George Karypis

Improved estimation of structure predictor quality (2009)

As the sequence identity between a pair of proteins decreases, alignment strategies that are based on sequence and/or sequence profiles become progressively less effective in identifying the correct...

DeRonne, Kevin W, Karypis, George

Abstract Background Methods that can automatically assess the quality of computationally predicted protein structures are important, as they enable the selection of the most accurate structure from...

Nikil Wale, George Karypis

Methods that can screen large databases to retrieve a struc-turally diverse set of compounds with desirable bioactivity prop-erties are critical in the drug discovery and development process. This...

Chapter 1 Partitioning and Load Balancing for Emerging Parallel Applications and Architectures (2008)

Karen D. Devine, Erik G. Boman, George Karypis

An important component of parallel scientific computing is partitioning – the assignment of work to processors. This assignment occurs at the start of a computation (“static ” partitioning)....

Abstract A Comparison of Document Clustering Techniques (2008)

Research Track Paper Efficient Closed Pattern Mining in the Presence of Tough Block Constraints ∗ (2008)

This paper presents the results of an experimental study of some common document clustering techniques. In particular, we compare the two main approaches to document clustering, agglomerative...

Krishna Gade, Jianyong Wang, George Karypis

Various constrained frequent pattern mining problem formulations and associated algorithms have been developed that enable the user to specify various itemset-based constraints that better capture...

Efficient Algorithms for Creating Product Catalogs * (2008)

TOPTMH: Topology Predictor for (2008)

For the purposes of this paper we define a catalog to be a promotional catalog, i.e., a collection of products (items) presented to a customer with the hope of encouraging a purchase. The single...

Rezwan Ahmed, Huzefa Rangwala, George Karypis, Rezwan Ahmed, Huzefa Rangwala, George Karypis

Alpha-helical transmembrane proteins mediate many key biological processes and represent 20–30 % of all genes in many organisms. Due to the difficulties in experimentally determining their...

Abstract Finding Frequent Patterns in a Large Sparse Graph ∗ (2008)

Multilevel-way Document Clustering: Experiments & Analysis¡ (2008)

This paper presents two algorithms based on the horizontal and vertical pattern discovery paradigms that find the connected subgraphs that have a sufficient number of edgedisjoint embeddings in a...

Krishna Gade, George Karypis

In recent years, we have witnessed a tremendous growth in the volume of text documents available on the Internet, digital libraries, news sources and company-wide intranets. This has led to an...

SCIENCE AND TECHNOLOGY TEXT MINING: WIRELESS LANS By (2008)

N. Kostoff, Mr. Rene Tshiteya, Mr. Jesse Stump, Mr. Guido Malpohl, Dr. George Karypis

Page 1 Database Tomography (DT) is a textual database analysis system consisting of two major components: 1) algorithms for extracting multi-word phrase frequencies and phrase proximities (physical...

1 Contents (2008)

Incremental window-based protein sequence alignment algorithms (2008)

Discriminating Subsequence Discovery for Sequence Clustering ∗ (2008)

Motivation: Protein sequence alignment plays a critical role in computational biology as it is an integral part in many analysis tasks designed to solve problems in comparative genomics, structure...

Jianyong Wang, Yuzhou Zhang, Lizhu Zhou, George Karypis

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Incremental window-based protein sequence alignment algorithms (2008)

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Huzefa Rangwala, Huzefa Rangwala, George Karypis, George Karypis

Motivation: Protein sequence alignment plays a critical role in computational biology as it is an integral part in many analysis tasks designed to solve problems in comparative genomics, structure...

Evaluation of Techniques for Classifying Biological Sequences ∗ (2008)

Problem Characterization • Temporal (2008)

In recent years we have witnessed an exponential increase in the amount of biological information, either DNA or protein sequences, that has become available in public databases. This has been...

Associate Editors (2008)

Eui-hong Han, George Karypis, Vipin Kumar, Bamshad Mobasher, Mining Charu, C. Aggarwal, ...

The Bulletin of the Technical Committee on Data Engineering is published quarterly and is distributed to all TC members. Its scope includes the design, implementation, modelling, theory and...

Benjamin Mayer, Huzefa Rangwala, Rohit Gupta, Jaideep Srivastava, George Karypis, Vipin Kumar, ...

a classification model to predict liver fibrosis stage based on combinations of common laboratory tests, obtained over time during routine patient care • Find unknown novel patterns in a large...

Steve Reinhardt, George Karypis

Graphs capture the essential elements of many problems broadly defined as searching or categorizing. With the rapid increase of data volumes from sensors, many application disciplines need to process...

BIOINFORMATICS (2008)

Dynamic Repartitioning of Adaptively Refined Meshes Dynamic Repartitioning of Adaptively Refined (2008)

Incremental window-based protein sequence alignment algorithms Vol. 23 ECCB 2006, pages e17–e23 doi:10.1093/bioinformatics/btl297

Kirk Schloegel, George Karypis

One ingredient which is viewed as vital to the successful conduct of many large-scale numerical simulations is the ability to dynamically repartition the underlying adaptive finite element mesh among...

fRMSDAlign: Protein Sequence Alignment Using Predicted Local Structure Information for Pairs with Low Sequence Identity (2008)

ARTICLE NO. PC971410 Multilevel Diffusion Schemes for Repartitioning of Adaptive Meshes 1 (2008)

As the sequence identity between a pair of proteins decreases, alignment strategies that are based on sequence and/or sequence profiles become progressively less effective in identifying the correct...

Selective Markov Models for Predicting Web-Page Accesses ∗ (2008)

For a large class of irregular mesh applications, the structure of the mesh changes from one phase of the computation to the next. Eventually, as the mesh evolves, the adapted mesh has to be...

By (2008)

Mexico Core Competencies, N. Kostoff, Héctor D. Cortés, Temixco Mor México, ...

1

On efficiently summarizing categorical databases. Knowledge and Information Systems, 9(1):19–37, January 2006. Author Biographies Vipin Kumar is currently William Norris Professor and Head of the Computer Science and Engineering Department at the Universi (2008)

The problem of predicting a user’s behavior on a web-site has gained importance due to the rapid growth of the world-wide-web and the need to personalize and influence a user’s browsing...

Jianyong Wang, George Karypis, J. Wang, G. Karypis (b

Abstract Frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. In recent years, several studies have also extended its application...

Automated approaches for classifying structures ∗ (2008)

Algorithms for Graph Partitioning and Fill Reducing Ordering for Domain Decomposition Methods ∗ (2008)

In this paper we study the problem of classifying chemical compound datasets. We present an algorithm that first mines the chemical compound dataset to discover discriminating sub-structures; these...

DOI: 10.1007/s10618-005-0003-9 Finding Frequent Patterns in a Large Sparse Graph ∗ (2008)

This paper focuses on domain decomposition-based numerical simulations whose subproblems corresponding to the various subdomains are solved using sparse direct factorization methods (e.g., FETI)....

Predicting the Performance of Randomized Parallel Search: An Application to Robot Motion Planning (2008)

Abstract. Graph-based modeling has emerged as a powerful abstraction capable of capturing in a single and unified framework many of the relational, spatial, topological, and other characteristics...

Daniel J. Challou, Maria Gini, Vipin Kumar, George Karypis

Abstract. In this paper we discuss methods for predicting the performance of any formulation of randomized parallel search, and propose a new performance prediction method that is based on obtaining...

The algorithms described in this paper are implemented by the ‘PARMETIS: Parallel Graph Partitioning and Sparse Matrix Ordering Library’. (2008)

Paper Number: 432 Multilevel Refinement for Hierarchical Clustering ∗ (2008)

Graph partitioning has been shown to be an effective way to divide a large computation over an arbitrary number of processors. A good partitioning can ensure load balance and minimize the...

PSPASES: Building a High Performance Scalable Parallel Direct Solver for Sparse Linear Systems \Lambda (2008)

Hierarchical methods are well known clustering technique that can be potentially very useful for various data mining tasks. A hierarchical clustering scheme produces a sequence of clusterings in...

Mahesh Joshi, George Karypis, Vipin Kumar, Anshul Gupta, Fred Gustavson

MultilevelAlgorithmsforGeneratingCoarseGridsfor (2008)

Partitioning Algorithms for Simultaneously Balancing Iterative and Direct Methods (2008)

Geometric Multigrid methods have gained widespread acceptance for solving large systems of linear equations, especially for structured grids. One of the challenges in successfully extending these...

PSPASES: An E cient and Scalable Parallel Sparse Direct Solver (2008)

This paper focuses on domain decomposition-based numerical simulations whose subproblems corresponding to the various subdomains are solved using sparse direct factorization methods (e.g., FETI)....

Mahesh Joshi, George Karypis, Vipin Kumar, Anshul Gupta, Fred Gustavson

Many problems in engineering and scienti c domains require solving large sparse systems of linear equations, as a computationally intensive steptowards the nal solution. It has long beenachallenge to...

Paper Number: 432 Multilevel Refinement for Hierarchical Clustering* (2008)

ABSTRACT ClustKNN: A Highly Scalable Hybrid Model- & Memory-Based CF Algorithm (2008)

Al Mamunur Rashid, Shyong K. Lam, George Karypis, John Riedl

Collaborative Filtering (CF)-based recommender systems are indispensable tools to find items of interest from the unmanageable number of available items. Moreover, companies who deploy a CF-based...

E cient Parallel Algorithms for Mining Associations? (2008)

Accepted in 9th Heterogeneous Computing Workshop (HCW 2000) Load Balancing Across Near-Homogeneous Multi-Resource Servers £ (2008)

Abstract. The problem of mining hidden associations present in the large amounts of data has seen widespread applications in many practical domains such as customer-oriented planning and marketing,...

William Leinberger, George Karypis, Vipin Kumar, Rupak Biswas

An emerging model for computational grids interconnects similar multi-resource servers from distributed sites. A job submitted to the grid can be executed by any of the servers; however, resource...

WebACE: A Web Agent for Document Categorization and Exploration (2007)

George Karypis, Vipin Kumar, Bamshad Mobasher, Jerome Moore

We propose an agent for exploring and categorizing documents on the World Wide Web. The heart of the agent is an automatic categorization of a set of documents, combined with a process for generating...

Selective Markov Models for Predicting Web-Page Accesses ∗ (2007)

Selective Markov Models for Predicting Web-Page Accesses # (2007)

The problem of predicting a user’s behavior on a web-site has gained importance due to the rapid growth of the world-wide-web and the need to personalize and influence a user’s browsing...

Technical Report #00-046 Evaluation of Item-Based Top-N Recommendation Algorithms ∗ (2007)

The problem of predicting a user's behavior on a web-site has gained importance due to the rapid growth of the world-wide-web and the need to personalize and influence a user's browsing...

Mahesh V. Joshi, George Karypis

The explosive growth of the world-wide-web and the emergence of e-commerce has led to the development of recommender systems—a personalized information filtering technology used to identify a set...

Vipin Kumar (2007)

Discovery of predictive sequential associations among events is becoming increasingly useful and essential in manyscientific and commercial domains. Enormous sizes of available datasets and possibly...

Parallel Algorithms for Mining Sequential Associations: Issues and Challenges (2007)

Multi-Resource Aware Partitioning Algorithms for FPGAs with Heterogeneous Resources ∗ ABSTRACT (2007)

Discovery of predictive sequential associations among events is becoming increasingly useful and essential in many scientific and commercial domains. Enormous sizes of available datasets and possibly...

Abhishek Ranjan, Salil Raje, George Karypis

As FPGA densities increase, partitioning-based FPGA placement approaches are becoming increasingly important as they can be used to provide high-quality and computationally scalable solutions....

Multi-Resource Aware Partitioning Algorithms for FPGAs with Heterogeneous Resources # (2007)

Abhishek Ranjan, Salil Raje, George Karypis

As FPGA densities increase, partitioning-based FPGA placement approaches are becoming increasingly important as they can be used to provide high-quality and computationally scalable solutions....

Finding Frequent Patterns Using Length-Decreasing Support Constraints ∗ (2007)

Parallel Formulations of Tree-Projection-Based Sequence Mining Algorithm * (2007)

Finding prevalent patterns in large amount of data has been one of the major problems in the area of data mining. Particularly, the problem of finding frequent itemset or sequential patterns in very...

High Performance Computing Research Center contract number DAAH04-95-C-0008. Contents (2007)

Discovery of sequential patterns is becoming increasingly useful and essential in many scientific and commercial domains. Enormous sizes of available datasets and possibly large number of mined...

For Multigrid Mefhods, Irene Moulitsas, George Karypis

Finding Frequent Patterns Using Length-Decreasing Support Constraints * (2007)

Parallel Formulations of Tree-Projection-Based Sequence Mining Algorithm ∗ (2007)

Finding prevalent patterns in large amount of data has been one of the major problems in the area of data mining. Particularly, the problem of finding frequent itemset or sequential patterns in very...

Evaluation of Techniques for Classifying Biological Sequences # (2007)

Discovery of sequential patterns is becoming increasingly useful and essential in many scientific and commercial domains. Enormous sizes of available datasets and possibly large number of mined...

Evaluation of Techniques for Classifying Biological Sequences ∗ (2007)

In recent years we have witnessed an exponential increase in the amount of biological information, either DNA or protein sequences, that has become available in public databases. This has been...

Multilevel Algorithms for Generating Coarse Grids for (2007)

In recent years we have witnessed an exponential increase in the amount of biological information, either DNA or protein sequences, that has become available in public databases. This has been...

Multigrid Methods, Irene Moulitsas, George Karypis

Geometric Multigrid methods have gained widespread acceptance for solving large systems of linear equations, especially for structured grids. One of the challenges in successfully extending these...

Mining Temporal Relationships with Multiple Granularities in Time Sequences........................... (2007)

Eui-hong Han, George Karypis, Vipin Kumar, Bamshad Mobasher, Mining Charu, C. Aggarwal, ...

Automated approaches for classifying structures # (2007)

Evaluation of Hierarchical Clustering Algorithms for (2007)

In this paper we study the problem of classifying chemical compound datasets. We present an algorithm that first mines the chemical compound dataset to discover discriminating sub-structures; these...

Automated approaches for classifying structures ∗ (2007)

Fast and high-quality document clustering algorithms play an important role in providing intuitive navigation and browsing mechanisms by organizing large amounts of information into a small number of...

Multilevel Algorithms for Generating Coarse Grids for (2007)

In this paper we study the problem of classifying chemical compound datasets. We present an algorithm that first mines the chemical compound dataset to discover discriminating sub-structures; these...

Multigrid Methods, Irene Moulitsas, George Karypis

Geometric Multigrid methods have gained widespread acceptance for solving large systems of linear equations, especially for structured grids. One of the challenges in successfully extending these...

Appears in the 1st IEEE Conference on Data Mining (2001) Frequent Subgraph Discovery (2007)

Gene Classication using Expression Proles: A Feasibility Study (2007)

Over the years, frequent itemset discovery algorithms have been used to solve various interesting problems. As data mining techniques are being increasingly applied to non-traditional domains,...

Mahesh V. Joshi, George Karypis

As various genome sequencing projects have already been completed or are near completion, genome researchers are shifting their focus from structural genomics to functional genomics. Functional...

Vipin Kumar (2007)

This paper proposes a universal formulation of sequential patterns, which unies and generalizes most of the previously proposed formulations such as the generalized patterns proposed by Srikant and...

Privacy Risks to Straddlers in Recommender Systems (2007)

Naren Ramakrishnan, Benjamin J. Keller, Batul J. Mirza, Ananth Y. Grama, George Karypis

We explore the conflict between personalization and privacy that arises from the existence of straddlers in a recommender system. A straddler is a person with eclectic tastes who rates products...

Vipin Kumar (2007)

Appears in the 1st IEEE Conference on Data Mining (2001) LPMiner: An Algorithm for Finding Frequent Itemsets Using Length-Decreasing Support Constraint (2007)

One of the important problems in data mining is discovering association rules from databases of transactions where each transaction consists of a set of items. The most time consuming operation in...

Appears in the 1st IEEE Conference on Data Mining (2001) LPMiner: An Algorithm for Finding Frequent Itemsets Using Length-Decreasing Support Constraint (2007)

Over the years, a variety of algorithms for nding frequent itemsets in very large transaction databases have been developed. The key feature in most of these algorithms is that they use a constant...

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Over the years, a variety of algorithms for finding frequent itemsets in very large transaction databases have been developed. The key feature in most of these algorithms is that they use a constant...

Badrul Sarwar, George Karypis, Joseph Konstan, John Riedl

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Performance and Scalability of the Parallel Simplex Method for (2007)

Dense Linear Programming, George Karypis, Vipin Kumar

George Karypis and Vipin Kumar Computer Science Department University of Minnesota May 21, 1994 1

Mukund Deshpande, Michihiro Kuramochi and George Karypis (2007)

Partitioning Algorithms for Simultaneously Balancing Iterative and Direct Methods (2007)

In this paper we study the problem of classifying chemical compound datasets. We present an algorithm that first mines the chemical compound dataset to discover discriminating sub-structures; these...

Data Mining in Bioinformatics (BIOKDD) (2007)

This paper focuses on domain decomposition-based numerical simulations whose subproblems corresponding to the various subdomains are solved using sparse direct factorization methods (e.g., FETI)....

Zaki, Mohammed J, Karypis, George, Yang, Jiong

No abstract available.

Incremental window-based protein sequence alignment algorithms (2007)

Data Mining in Bioinformatics (BIOKDD). (2007)

Motivation: Protein sequence alignment plays a critical role in computational biology as it is an integral part in many analysis tasks designed to solve problems in comparative genomics, structure...

Zaki, Mohammed J, Karypis, George, Yang, Jiong

Transcriptome dynamics-based operon prediction and verification in Streptomyces coelicolor (2007)

Charaniya, Salim, Mehra, Sarika, Lian, Wei, Jayapal, Karthik P., Karypis, George, Hu, Wei-Shou

Streptomyces spp. produce a variety of valuable secondary metabolites, which are regulated in a spatio-temporal manner by a complex network of inter-connected gene products. Using a compilation of...

Building multiclass classifiers for remote homology detection and fold recognition (2006)

Multilevel algorithms for partitioning power-law graphs (2006)

Abstract Background Protein remote homology detection and fold recognition are central problems in computational biology. Supervised learning algorithms based on support vector machines are currently...

Amine Abou-rjeili, Amine Abou-rjeili, George Karypis, George Karypis

Graph partitioning is an enabling technology for parallel processing as it allows for the effective decomposition of unstructured computations whose data dependencies correspond to a large sparse and...

Comparison of descriptor spaces for chemical compound retrieval and classification (2006)

Nikil Wale, Ian A. Watson, George Karypis

Abstract. In recent years the development of computational techniques that build models to correctly assign chemical compounds to various classes or to retrieve potential drug-like compounds has been...

Coherent closed quasi-clique discovery from large dense graph databases (2006)

Zhiping Zeng, Jianyong Wang, Lizhu Zhou, George Karypis

Frequent coherent subgraphscan provide valuable knowledge about the underlying internal structure of a graph database, and mining frequently occurring coherent subgraphs from large dense graph...

Architecture aware partitioning algorithms (2006)

Architecture aware partitioning algorithms (2006)

Existing partitioning algorithms provide limited support for load balancing simulations that are performed on heterogeneous parallel computing platforms. On such architectures, effective load...

Opening Remarks (2006)

Mohammed J. Zaki, George Karypis, Jiong Yang, Mohammed J. Zaki, George Karypis, Jiong Yang

Data Mining is the process of automatic discovery of novel and understandable models and patterns from large amounts of data. Bioinformatics is the science of storing, analyzing, and utilizing...

Irene Moulitsas, Irene Moulitsas, George Karypis, George Karypis

Existing partitioning algorithms provide limited support for load balancing simulations that are performed on heterogeneous parallel computing platforms. On such architectures, effective load...

BioMed Central (2006)

Bmc Bioinformatics, Huzefa Rangwala, George Karypis

Research article Building multiclass classifiers for remote homology detection and fold recognition

HARMONY: Efficiently mining the best rules for classification (2005)

Jianyong Wang, George Karypis

Many studies have shown that rule-based classification algorithms perform well in classifying categorical and sparse high-dimensional databases. However, a fundamental limitation with many rule-based...

Profile based direct kernels for remote homology detection and fold recognition (2005)

Huzefa Rangwala, Huzefa Rangwala, George Karypis, George Karypis

Motivation: Remote homology detection between protein sequences is a central problem in computational biology. Supervised learning algorithms based on support vector machines are currently the most...

BY (2005)

Navaratnasothie Selvakkumaran, Dr. George Karypis

is to certify that I have examined this copy of a doctoral dissertation by

Downloaded from (2005)

Ronald N. Kostoff, Héctor D. Cortés, Charles Smith, Andrew Smith, Caroline Wagner, ...

Clustering methodologies for identifying country core

Effective Document Clustering for Large Heterogeneous Law Firm Collections ABSTRACT (2005)

Jack G. Conrad, Ying Zhao, Khalid Al-kofahi, George Karypis, Jack G. Conrad, Khalid Al-kofahi

Computational resources for research in legal environments have historically implied remote access to large databases of legal documents such as case law, statutes, law reviews and administrative...

Additional Reviewers (2005)

Siegfried Nijssen, Thorsten Meinl, George Karypis, Siegfried Nijssen, Thorsten Meinl, George Karypis, ...

Proceedings of the 3 rd International Workshop on

Profile-based direct kernels for remote homology detection and fold recognition (2005)

Profile based direct kernels for remote homology detection and fold recognition (2005)

Motivation: Protein remote homology detection is a central problem in computational biology. Supervised learning algorithms based on support vector machines are currently one of the most effective...

Item-based top-n recommendation algorithms (2004)

Motivation: Protein remote homology detection is a central problem in computational biology. Supervised learning algorithms based on support vector machines are currently one of the most effective...

Mukund Deshpande, George Karypis

The explosive growth of the world-wide-web and the emergence of e-commerce has led to the development of recommender systems---a personalized information filtering technology used to identify a set...

Efficient closed pattern mining in the presence of tough block constraints (2004)

Krishna Gade, Jianyong Wang, George Karypis

In recent years, various constrained frequent pattern mining problem formulations and associated algorithms have been developed that enable the user to specify various itemsetbased constraints that...

BAMBOO: Accelerating closed itemset mining by deeply pushing the length-decreasing support constraint (2004)

Jianyong Wang, George Karypis

Previous study has shown that mining frequent patterns with length-decreasing support constraint is very helpful in removing some uninteresting patterns based on the observation that short patterns...

Item-based top-n recommendation algorithms (2004)

Mukund Deshpande, George Karypis

The explosive growth of the world-wide-web and the emergence of e-commerce has led to the development of recommender systems—a personalized information filtering technology used to identify a set...

Efficient closed pattern mining in the presence of tough block constraints (2004)

Krishna Gade, Krishna Gade, Jianyong Wang, Jianyong Wang, George Karypis, George Karypis

In recent years, various constrained frequent pattern mining problem formulations and associated algorithms have been developed that enable the user to specify various itemsetbased constraints that...

Implicit Heuristics to Mitigate Interconnect Congestion in a Multilevel Placement Framework (2004)

Navaratnasothie Selvakkumaran, Phiroze Parakh, Abhishek Ranjan, George Karypis, Navaratnasothie Selvakkumaran, Phiroze Parakh, ...

The congestion minimization techniques have become more important due to the shrinking geometries and “taller” interconnects, causing numerous design convergence problems. Also, multilevel...

Partitioning Algorithms for FPGAs with Heterogeneous Resources (2004)

Navaratnasothie Selvakkumaran, Abhishek Ranjan, Salil Raje, George Karypis, Navaratnasothie Selvakkumaran, Abhishek Ranjan, ...

As FPGA densities increase, partitioning-based FPGA placement approaches are becoming increasingly impor-tant as they can be used to provide high-quality and computationally scalable placement...

Partitioning Algorithms for Simultaneously Balancing Iterative and Direct Methods (2004)

Irene Moulitsas, George Karypis, Irene Moulitsas, George Karypis

This paper focuses on domain decomposition-based numerical simulations whose subproblems corresponding to the various subdomains are solved using sparse direct factorization methods (e.g., FETI)....

gCLUTO - An Interactive Clustering, Visualization, and Analysis System (2004)

Matt Rasmussen, George Karypis

Clustering algorithms are exploratory data analysis tools that have proved to be essential for gaining valuable insights on various aspects and relationships of the underlying systems. In this paper...

gCLUTO - An Interactive Clustering, Visualization, and Analysis System (2004)

Matt Rasmussen, George Karypis

Clustering algorithms are exploratory data analysis tools that have proved to be essential for gaining valuable insights on various aspects and relationships of the underlying systems. In this paper...

Item Based Top-N Recommendation Algorithms (2004)

Mukund Deshpande, George Karypis

this paper we present one such class of model-based recommendation algorithms that first determines the similarities between the various items and then uses them to identify the set of items to be...

Efficient Closed Pattern Mining in the Presence of Tough Block Constraints (2004)

Krishna Gade, Jianyong Wang, George Karypis

In recent years, various constrained frequent pattern mining problem formulations and associated algorithms have been developed that enable the user to specify various itemsetbased constraints that...

Finding Functionally Related Genes by Local and Global Analysis of Medline Abstracts (2004)

Sigve Nakken, Sigve Nakken, Christopher Kauffman, Christopher Kauffman, George Karypis, George Karypis

Discovery of biological relationships between genes is one of the keys to understanding the complex functional nature of the human genome. Currently, most of the knowledge about interrelating genes...

Soft Clustering Criterion Functions for Partitional Document Clustering (2004)

Soft Clustering Criterion Functions for Partitional Document Clustering (2004)

Recently published studies have shown that partitional clustering algorithms that optimize certain criterion functions, which measure key aspects of inter- and intra-cluster similarity, are very...

Finding Frequent Patterns in a Large Sparse Graph (2004)

Recently published studies have shown that partitional clustering algorithms that optimize certain criterion functions, which measure key aspects of inter- and intra-cluster similarity, are very...

Multi-resource aware partitioning algorithms for FPGAs with heterogeneous resources (2004)

This paper presents two algorithms based on the horizontal and vertical pattern discovery paradigms that find the connected subgraphs that have a sufficient number of edgedisjoint embeddings in a...

Navaratnasothie Selvakkumaran, Abhishek Ranjan, Salil Raje, George Karypis, Abhishek Ranjan

As FPGA densities increase, partitioning-based FPGA placement approaches are becoming increasingly important as they can be used to provide high-quality and computationally scalable solutions....

Perimeter-degree: a Priori Metric for Directly Measuring and Homogenizing Interconnection Complexity (2003)

Navaratnasothie Selvakkumaran, Phiroze N. Parakh, George Karypis

In this paper, we describe an accurate metric (perimeter-degree) for measuring interconnection complexity and effective use of it for controlling congestion in a multilevel framework....

THETO: A Fast and High-Quality Partitioning Driven Global Placer (2003)

Navaratnasothie Selvakkumaran, George Karypis

Partitioning driven placement approaches are often preferred for fast and scalable solutions to large placement problems. However, due to the inaccuracy of representing wirelength objective by cut...

Prediction of contact maps using support vector machines (2003)

GREW—A Scalable Frequent Subgraph Discovery Algorithm (2003)

Contact map prediction is of great interest for its application in fold recognition and protein 3D structure determination. In this paper we present a contact-map prediction algorithm that employs...

Multi-constraint mesh partitioning for contact/impact computations (2003)

Existing algorithms that mine graph datasets to discover patterns corresponding to frequently occurring subgraphs can operate efficiently on graphs that are sparse, contain a large number of...

George Karypis, George Karypis

We present a novel approach for decomposing contact/impact computations in which the mesh elements come in contact with each other during the course of the simulation. Effective decomposition of...

Multi-objective hypergraph partitioning algorithms for cut and maximum subdomain degree minimization (2003)

Navaratnasothie Selvakkumaran, George Karypis, Navaratnasothie Selvakkumaran, George Karypis

In this paper we present a family of multi-objective hypergraph partitioning algorithms based on the multilevel paradigm, which are capable of producing solutions in which both the cut and the...

THETO: A Fast and High-Quality Partitioning Driven Global Placer (2003)

Navaratnasothie Selvakkumaran, George Karypis, Navaratnasothie Selvakkumaran, George Karypis

Partitioning driven placement approaches are often preferred for fast and scalable solutions to large placement problems. However, due to the inaccuracy of representing wirelength objective by cut...

Frequent sub-structure-based approaches for classifying chemical compounds (2003)

Frequent sub-structure-based approaches for classifying chemical compounds (2003)

In this paper we study the problem of classifying chemical compound datasets. We present a sub-structure-based classification algorithm that decouples the sub-structure discovery process from the...

Clustering in the life sciences (2003)

In this paper we study the problem of classifying chemical compound datasets. We present a sub-structure-based classification algorithm that decouples the sub-structure discovery process from the...

THETO: A Fast and High-Quality Partitioning Driven Global Placer (2003)

Clustering is the task of organizing a set of objects into meaningful groups. These groups can be disjoint, overlapping, or organized in some hierarchical fashion. The key element of clustering is...

Navaratnasothie Selvakkumaran, George Karypis

Partitioning driven placement approaches are often preferred for fast and scalable solutions to large placement problems. However, due to the inaccuracy of representing wirelength objective by cut...

Prediction of Contact Maps Using Support Vector Machines (2003)

Perimeter-Degree: A Priori Metric for Directly Measuring and Homogenizing Interconnection Complexity in Multilevel Placement (2003)

Contact map prediction is of great interest for its application in fold recognition and protein 3D structure determination. In this paper we present a contact-map prediction algorithm that employs...

Navaratnasolhie Selvakkumaran, Phiroze N. Parakh, George Karypis

In this paper, we describe an accurate metric (perimeter-degree) for measuring interconnection complexity and effective use of it for controlling congestion in a multilevel framework....

wCLUTO: A Web-Enabled Clustering Toolkit (2003)

Matthew Rasmussen, Mukund Deshpande, George Karypis, James Johnson, John A. Crow, Ernest F. Retzel

As structural and functional genomics efforts provide the biological community with ever-broadening sets of interrelated data, the need to explore such complex information for subtle relationships...

wCLUTO: A Web-Enabled Clustering Toolkit (2003)

Matthew Rasmussen, Mukund Deshpande, George Karypis, James Johnson, John A. Crow, Ernest F. Retzel

As structural and functional genomics efforts provide the biological community with ever-broadening sets of interrelated data, the need to explore such complex information for subtle relationships...

Multi-Constraint Mesh Partitioning for Contact/Impact Computations (2003)

Perimeter-Degree: A Priori Metric for Directly Measuring and Homogenizing Interconnection Complexity in Multilevel Placement (2003)

We present a novel approach for decomposing contact/impact computations in which the mesh elements come in contact with each other during the course of the simulation. Effective decomposition of...

Navaratnasothie Selvakkumaran, Phiroze N. Parakh, George Karypis

In this paper, we describe an accurate metric (perimeter-degree) for measuring interconnection complexity and effective use of it for controlling congestion in a multilevel framework....

Multi-Objective Hypergraph Partitioning Algorithms for Cut and Maximum Subdomain Degree Minimization (2003)

Navaratnasothie Selvakkumaran, George Karypis

In this paper we present a family of multi-objective hypergraph partitioning algorithms based on the multilevel paradigm, which are capable of producing solutions in which both the cut and the...

Abstract Finding Frequent Patterns in a Large Sparse Graph ∗ (2003)

Michihiro Kuramochi, George Karypis, Michihiro Kuramochi, George Karypis

This paper presents two algorithms based on the horizontal and vertical pattern discovery paradigms that find the connected subgraphs that have a sufficient number of edgedisjoint embeddings in a...

GREW—A Scalable Frequent Subgraph Discovery Algorithm (2003)

Michihiro Kuramochi, Michihiro Kuramochi, George Karypis, George Karypis

Existing algorithms that mine graph datasets to discover patterns corresponding to frequently occurring subgraphs can operate efficiently on graphs that are sparse, contain a large number of...

Finding Frequent Patterns in a Large Sparse Graph (2003)

3.2 Partitioning Meshes Directly....................................... 7 (2003)

This paper presents two algorithms based on the horizontal and vertical pattern discovery paradigms that find the connected subgraphs that have a sufficient number of edgedisjoint embeddings in a...

George Karypis, Kirk Schloegel, Vipin Kumar

∗ PARMETIS is copyrighted by the regents of the University of Minnesota. 1

Expert Agreement and Content Based Reranking in a Meta Search Environment using Mearf (2002)

Uygar Oztekin, B., Karypis, George, Kumar, Vipin

Recent increase in the number of search engines on the Web and the availability of meta search engines that can query multiple search engines makes it important to find effective methods for...

Using conjunction of attribute values for classification (2002)

Mukund Deshp, Mukund Deshp, George Karypis, George Karypis

Advances in the efficient discovery of frequent itemsets in large databases have led to the development of a number of schemes that use frequent itemsets to aid in the development of accurate and...

An efficient algorithm for discovering frequent subgraphs (2002)

Automated Approaches for Classifying Structures (2002)

Abstract — Over the years, frequent itemset discovery algorithms have been used to find interesting patterns in various application areas. However, as data mining techniques are being increasingly...

Mukund Deshp, Michihiro Kuramochi, George Karypis, Mukund Deshp, Michihiro Kuramochi, George Karypis

In this paper we study the problem of classifying chemical compound datasets. We present an algorithm that first mines the chemical compound dataset to discover discriminating sub-structures; these...

Machines ∗ (2002)

Ying Zhao, George Karypis, Ying Zhao, George Karypis

Contact map prediction is of great interests for its application in fold recognition and protein 3D structure determination. In particular, we focusd on predicting non-local interactions in this...

An efficient algorithm for discovering frequent subgraphs (2002)

Using conjunction of attribute values for classification (2002)

Abstract—Over the years, frequent itemset discovery algorithms have been used to find interesting patterns in various application areas. However, as data mining techniques are being increasingly...

Using conjunction of attribute values for classification (2002)

Advances in the efficient discovery of frequent itemsets in large databases have led to the development of a number of schemes that use frequent itemsets to aid in the development of accurate and...

SLPMiner: An Algorithm for Finding Frequent Sequential Patterns Using Length-Decreasing Support Constraint (2002)

Advances in the efficient discovery of frequent itemsets in large databases have led to the development of a number of schemes that use frequent itemsets to aid in the development of accurate and...

Discovering frequent geometric subgraphs (2002)

Over the years, a variety of algorithms for finding frequent sequential patterns in very large sequential databases have been developed. The key feature in most of these algorithms is that they use a...

An efficient algorithm for discovering frequent subgraphs (2002)

As data mining techniques are being increasingly applied to non-traditional domains, existing approaches for finding frequent itemsets cannot be used as they cannot model the requirement of these...

Evaluation of hierarchical clustering algorithms for document datasets (2002)

Over the years, frequent itemset discovery algorithms have been used to find interesting patterns in various application areas. However, as data mining techniques are being increasingly applied to...

Discovering frequent geometric subgraphs (2002)

Fast and high-quality document clustering algorithms play an important role in providing intuitive navigation and browsing mechanisms by organizing large amounts of information into a small number of...

An efficient algorithm for discovering frequent subgraphs (2002)

As data mining techniques are being increasingly applied to non-traditional domains, existing approaches for finding fi'equent itemsets cannot be used as they cannot model the requirement of...

SLPMiner: An Algorithm for Finding Frequent Sequential Patterns Using Length-Decreasing Support Constraint (2002)

Over the years, frequent itemset discovery algorithms have been used to find interesting patterns in various application areas. However, as data mining techniques are being increasingly applied to...

When being weak is brave: privacy issues in recommender systems (2002)

Over the years, a variety of algorithms for finding frequent sequential patterns in very large sequential databases have been developed. The key feature in most of these algorithms is that they use a...

Naren Ramakrishnan, Benjamin J. Keller, Batul J. Mirza, Ananth Y. Grama, George Karypis

We explore the conflict between personalization and privacy that arises from the existence of weak ties. A weak tie is an unexpected connection that provides serendipitous recommendations. However,...

When being weak is brave: privacy issues in recommender systems (2002)

Naren Ramakrishnan, Benjamin J. Keller, Batul J. Mirza, Ananth Y. Grama, George Karypis

We explore the conflict between personalization and privacy that arises from the existence of weak ties. A weak tie is an unexpected connection that provides serendipitous recommendations. However,...

Recommender Systems for Large-scale E-Commerce: Scalable Neighborhood Formation Using Clustering (2002)

Badrul M. Sarwar, George Karypis, Joseph Konstan, John Riedl

Recommender syPx4fl apply knowledge discovery techniques to the problem of making personalized product recommendations during a live customer interaction. These sye ems, especially the k-nearest...

Hierarchical Clustering Algorithms for Document Datasets (2002)

Multilevel Hypergraph Partitioning (2002)

Fast and high-quality document clustering algorithms play an important role in providing intuitive navigation and browsing mechanisms by organizing large amounts of information into a small number of...

Multi-objective circuit partitioning for cutsize and path-based delay minimization (2002)

Introduction Hypergraph partitioning is an important problem with extensive application to many areas, including VLSI design [Alpert and Kahng, 1995], efficient storage of large databases on disks...

Cristinel Ababei, Navaratnasothie Selvakkumaran, Kia Bazargan, George Karypis

Abstract – In this paper we present multi-objective hMetis partitioning for simultaneous cutsize and circuit delay minimization. We change the partitioning process itself by introducing a new...

An efficient algorithm for discovering frequent subgraphs (2002)

Michihiro Kuramochi, George Karypis, George Karypis

number DAAH04-95-C-0008. Access to computing facilities was provided by the Minnesota Supercomputing Insti-tute. † An earlier version of this work appeared in [29]. Over the years, frequent itemset...

An efficient algorithm for discovering frequent subgraphs (2002)

Hierarchical Clustering Algorithms for Document Datasets (2002)

Over the years, frequent itemset discovery algorithms have been used to find interesting patterns in various application areas. However, as data mining techniques are being increasingly applied to...

Ying Zhao And, Ying Zhao, George Karypis

Fast and high-quality document clustering algorithms play an important role in providing intuitive navigation and browsing mechanisms by organizing large amounts of information into a small number of...

When being Weak is Brave: Privacy in Recommender Systems (2001)

Ramakrishnan, Naren, Keller, Benjamin J., Mirza, Batul J., Grama, Ananth Y., Karypis, George

We explore the conflict between personalization and privacy that arises from the existence of weak ties. A weak tie is an unexpected connection that provides serendipitous recommendations. However,...

Item-based Collaborative Filtering Recommendation Algorithms (2001)

Sarwar, Badrul, Karypis, George, Konstan, Joseph, Riedl, John

Recommender systems apply knowledge discovery techniques to the problem of making personalized recommendations for information, products or services during a live interaction. These systems,...

Improving precategorized collection retrieval by using supervised term weighting schemes (2001)

Ying Zhao, Ying Zhao, George Karypis, George Karypis

The emergence of the world-wide-web has led to an increased interest in methods for searching for information. A key characteristic of many of the online document collections is that the documents...

Evaluation of Techniques for Classifying Biological Sequences ∗ (2001)

Mukund Deshp, George Karypis, Mukund Deshp, George Karypis

In recent years we have witnessed an exponential increase in the amount of biological information, either DNA or protein sequences, that has become available in public databases. This has been...

Improving precategorized collection retrieval by using supervised term weighting schemes (2001)

Serial Multilevel Coarse Grid Construction (2001)

The emergence of the world-wide-web has led to an increased interest in methods for searching for information. A key characteristic of many of the online document collections is that the documents...

Criterion functions for document clustering: Experiments and analysis (2001)

number DAAH04-95-C-0008. Access to computing facilities was provided by the Minnesota Supercomputing Institute.

Criterion functions for document clustering: Experiments and analysis (2001)

In recent years, we have witnessed a tremendous growth in the volume of text documents available on the Internet, digital libraries, news sources, and company-wide intranets. This has led to an...

Privacy risks in recommender systems (2001)

In recent years, we have witnessed a tremendous growth in the volume of text documents available on the Internet, digital libraries, news sources, and company-wide intranets. This has led to an...

Benjamin J. Keller, Batul J. Mirza, Ananth Y. Grama, George Karypis

Recommender system users who rate items across disjoint domains face a privacy risk analogous to the one that occurs with statistical database queries. Recommender systems have become important tools...

G.: Dynamic load balancing algorithms for sequence mining (2001)

Parallel tree projection algorithm for sequence mining (2001)

Discovery of sequential patterns is becoming increasingly useful and essential in many scienti c and commercial domains. Enormous sizes of available datasets and possibly large number of mined...

Valerie Guralnik, Nivea Garg, George Karypis

Discovery of sequential patterns is becoming increasingly useful and essential in many scientific and commercial domains. Enormous sizes of available datasets and possibly large number of mined...

Parallel tree projection algorithm for sequence mining (2001)

Valerie Guralnik, Nivea Garg, George Karypis

Discovery of sequential patterns is becoming increasingly useful and essential in many scienti c and commercial domains. Enormous sizes of available datasets and possibly large number of mined...

Frequent subgraph discovery (2001)

Gene Classification Using Expression Profiles: A Feasibility Study (2001)

Over the years, frequent itemset discovery algorithms have been used to solve various interesting problems. As data mining techniques are being increasingly applied to non-traditional domains,...

A scalable algorithm for clustering protein sequences (2001)

As various genome sequencing projects have already been completed or are near completion, genome researchers are shifting their focus from structural genomics to functional genomics. Functional...

Multilevel algorithms for generating coarse grids for multigrid methods (2001)

The enormous growth of public sequence databases and continuing addition of fully sequenced genomes has created many challenges in developing novel and scalable computational techniques for...

Multilevel algorithms for generating coarse grids for multigrid methods (2001)

Geometric Multigrid methods have gained widespread acceptance for solving large systems of linear equations, especially for structured grids. One of the challenges in successfully extending these...

A scalable algorithm for clustering sequential data (2001)

Geometric Multigrid methods have gained widespread acceptance for solving large systems of linear equations, especially for structured grids. One of the challenges in successfully extending these...

G.: Dynamic load balancing algorithms for sequence mining (2001)

Many scienti c and commercial domains have seen an enormous growth of data in recent years. Such data sets have inherent sequential nature. The clustering of such data is useful for various purposes....

Item-based collaborative filtering recommendation algorithms (2001)

Discovery of sequential patterns is becoming increasingly useful and essential in many scientific and commercial domains. Enormous sizes of available datasets and possibly large number of mined...

Badrul Sarwar, George Karypis, Joseph Konstan, John Riedl

Recommender systems apply knowledge discovery techniques to the problem of making personalized recommendations for information, products or services during a live interaction. These systems,...

Item-based collaborative filtering recommendation algorithms (2001)

Badrul Sarwar, George Karypis, Joseph Konstan, John Riedl

Recommender systems apply knowledge discovery techniques to the problem of making personalized recommendations for information, products or services during a live interaction. These systems,...

Evaluation of item-based top-N recommendation algorithms (2001)

Item-based collaborative filtering recommendation algorithms (2001)

The explosive growth of the world-wide-web and the emergence of e-commerce has led to the development of recommender systems---a personalized information filtering technology used to identify a set...

Badrul Sarwar, George Karypis, Joseph Konstan, John Riedl

(Submitted to the WWW10 Conference) Recommender systems apply knowledge discovery techniques to the problem of making personalized recommendations for information, products or services during a live...

Evaluation of Item-Based (2001)

Improve Precategorized Collection Retrieval by Using Supervised Term (2001)

The explosive growth of the world-wide-web and the emergence of e-commerce has led to the development of recommender systems---a personalized information filtering technology used to identify a set...

Weighting Schemes Ying, Ying Zhao, George Karypis

interest in methods for searching for information. A key characteristic of many of the online document collections is that the documents have predefined category information, for example, the variety...

Appears in the 1st IEEE Conference on Data Mining (2001) LPMiner: An Algorithm for Finding Frequent Itemsets Using Length-Decreasing Support Constraint (2001)

Over the years, a variety of algorithms for nding frequent itemsets in very large transaction databases have been developed. The key feature in most of these algorithms is that they use a constant...

1 Contents (2001)

Item-based collaborative filtering recommendation algorithms (2001)

Badrul Sarwar, George Karypis, Joseph Konstan, John Riedl

Recommender systems apply knowledge discovery techniques to the problem of making personalized recommendations for information, products or services during a live interaction. These systems,...

Load balancing across near-homogeneous multiresource servers (2000)

William Leinberger, William Leinberger, George Karypis, George Karypis, Vipin Kumar, Vipin Kumar, ...

An emerging model for computational grids interconnects similar multi-resource servers from distributed sites. A job submitted to the grid can be executed by any of the servers; however, resource...

A unified algorithm for load-balancing adaptive scientific simulations (2000)

Graph partitioning for high performance scientific simulations (2000)

inter-processorcommunicationsincurredduringtheiterativemesh-basedcomputationandthedatare-thecourseofthecomputation.Therepartitioningsshouldbecomputedsoastominimizeboththe...

Kirk Schloegel, George Karypis, Vipin Kumar, Morgan Kaufmann, Early Draft

Efficient parallel algorithms for mining associations (2000)

Concept indexing: A fast dimensionality reduction algorithm with applications to document retrieval and categorization (2000)

George Karypis, Euihong (sam Han, George Karypis

In recent years, we have seen a tremendous growth in the volume of text documents available on the Internet, digital libraries, news sources, and company-wide intranets. This has led to an increased...

Concept indexing: A fast dimensionality reduction algorithm with applications to document retrieval and categorization (2000)

A comparison of document clustering techniques (2000)

In recent years, we have seen a tremendous growth in the volume of text documents available on the Internet, digital libraries, news sources, and company-wide intranets. This has led to an increased...

Abstract A Comparison of Document Clustering Techniques (2000)

This paper presents the results of an experimental study of some common document clustering techniques: agglomerative hierarchical clustering and K-means. (We used both a “standard” K-means...

Michael Steinbach, George Karypis, Vipin Kumar, Michael Steinbach, George Karypis, Vipin Kumar

This paper presents the results of an experimental study of some common document clustering techniques. In particular, we compare the two main approaches to document clustering, agglomerative...

A unified algorithm for load-balancing adaptive scientific simulations (2000)

Application of dimensionality reduction in recommender systems–a case study (2000)

Adaptive scientific simulations require that periodic repartitioning occur dynamically throughout the course of the computation. The repartitionings should be computed so as to minimize both the...

Badrul M. Sarwar, George Karypis, Joseph A. Konstan, John T. Riedl

We investigate the use of dimensionality reduction to improve performance for a new class of data analysis software called “recommender systems”. Recommender systems apply knowledge discovery...

Centroid-based document classification: Analysis and experimental results (2000)

Fast supervised dimensionality reduction algorithm with applications to document categorization and retrieval (2000)

Abstract. In this paper we present a simple linear-time centroid-based document classification algorithm, that despite its simplicity and robust performance, has not been extensively studied and...

Analysis of recommendation algorithms for e-commerce (2000)

Retrieval techniques based on dimensionality reduction, such as Latent Semantic Indexing (LSI), have been shown to improve the quality of the information being retrieved by capturing the latent...

Badrul Sarwar, George Karypis, Joseph Konstan, John Riedl

Centroid-based document classification: Analysis and experimental results (2000)

Load balancing across near-homogeneous multiresource servers (2000)

In recent years we have seen a tremendous growth in the volume of text documents available on the Internet, digital libraries, news sources, and company-wide intranets. Automatic text categorization,...

William Leinberger, George Karypis, Vipin Kumar, Rupak Biswas

An emerging model for computational grids interconnects similar multi-resource servers from distributed sites. A job submitted to the grid can be executed by any of the servers; however, resource...

Concept indexing: A fast dimensionality reduction algorithm with applications to document retrieval and categorization (2000)

A unified algorithm for load-balancing adaptive scientific simulations (2000)

In recent years, we have seen a tremendous growth in the volume of text documents available on the Internet, digital libraries, news sources, and company-wide intranets. This has led to an increased...

Centroid-Based Document Classification: Analysis & Experimental Results (2000)

Adaptive scientific simulations require that periodic repartitioning occur dynamically throughout the course of the computation. The repartitionings should be computed so as to minimize both the...

Eui-Hong (Sam) Han, George Karypis

In recent years we have seen a tremendous growth in the volume of text documents available on the Internet, digital libraries, news sources, and company-wide intranets. Automatic text categorization,...

A Comparison of Document Clustering Techniques (2000)

Parallel Algorithms in Data Mining (2000)

This paper presents the results of an experimental study of some common document clustering techniques. In particular, we compare the two main approaches to document clustering, agglomerative...

Mahesh V. Joshi, Eui-Hong (Sam) Han, George Karypis, Vipin Kumar

Introduction Recent times have seen an explosive growth in the availability of various kinds of data. It has resulted in an unprecedented opportunity to develop automated data-driven techniques of...

Centroid-Based Document Classification: Analysis Experimental Results (2000)

Fast Dimensionality Reduction, George Karypis

In recent years we have seen a tremendous growth in the volume of text documents available on the Internet, digital libraries, news sources, and company-wide intranets. Automatic text categorization,...

Concept Indexing (2000)

In recent years, we have seen a tremendous growth in the volume of text documents available on the Internet, digital libraries, news sources, and company-wide intranets. This has led to an increased...

A Unified Algorithm for Load-balancing Adaptive Scientific Simulations (2000)

Kirk Schloegel And, Kirk Schloegel, George Karypis, Vipin Kumar

Adaptive scientific simulations require that periodic repartitioning occur dynamically throughout the course of the simulation. The computed repartitionings should minimize both the inter-processor...

A Feature Weight Adjustment Algorithm for Document Categorization (2000)

Shrikanth Shankar, George Karypis

In recent years we have seen a tremendous growth in the volume of text documents available on the Internet, digital libraries, news sources, and company-wide intra-nets. Automatic text...

Graph Partitioning for High Performance Scientific Simulations (2000)

Kirk Schloegel George, George Karypis, Vipin Kumar, J. Dongarra, I. Foster, G. Fox, ...

Contents 0.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 0.2 Modeling Mesh-based Computations as Graphs . . . . . . . . . . . . . . . ....

Evaluation of Item-Based Top-N Recommendation Algorithms (2000)

Analysis of Recommendation Algorithms for E-Commerce (2000)

The explosive growth of the world-wide-web and the emergence of e-commerce has led to the development of recommender systems---a personalized information filtering technology used to identify a set...

Badrul Sarwar, George Karypis, Joseph Konstan, John Rield

Recommender systems apply statistical and knowledge discovery techniques to the problem of making product recommendations during a live customer interaction and they are achieving widespread success...

Analysis of Recommendation Algorithms for E-Commerce (2000)

Badrul Sarwar, George Karypis, Joseph Konstan, John Riedl

Recommender systems apply statistical and knowledge discovery techniques to the problem of making product recommendations during a live customer interaction and they are achieving widespread success...

Application of Dimensionality Reduction in Recommender System - A Case Study (2000)

Badrul M. Sarwar, George Karypis, Joseph A. Konstan, John T. Riedl

We investigate the use of dimensionality reduction to improve performance for a new class of data analysis software called "recommender systems". Recommender systems apply knowledge...

Weight Adjustment Schemes for a Centroid Based Classifier (2000)

Shrikanth Shankar, George Karypis

In recent years we have seen a tremendous growth in the volume of text documents available on the Internet, digital libraries, news sources, and company-wide intra-nets. Automatic text...

Graph Partitioning for High Performance Scientific Simulations (2000)

Kirk Schloegel, George Karypis, Vipin Kumar, J. Dongarra, I. Foster, G. Fox, ...

Contents 0.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 0.2 Modeling Mesh-based Computations as Graphs . . . . . . . . . . . . . . . ....

Weight Adjustment Schemes for a Centroid Based Classifier (2000)

Shrikanth Shankar And, Shrikanth Shankar, George Karypis

In recent years we have seen a tremendous growth in the volume of text documents available on the Internet, digital libraries, news sources, and company-wide intra-nets. Automatic text...

Concept Indexing - A Fast Dimensionality Reduction Algorithm with Applications to Document Retrieval & Categorization (2000)

George Karypis, Eui-Hong (Sam) Han

In recent years, we have seen a tremendous growth in the volume of text documents available on the Internet, digital libraries, news sources, and company-wide intranets. This has led to an increased...

A Unified Algorithm for Load-balancing Adaptive Scientific Simulations (2000)

Graph Partitioning for High Performance Scientific Simulations (2000)

Adaptive scientific simulations require that periodic repartitioning occur dynamically throughout the course of the simulation. The computed repartitionings should minimize both the inter-processor...

Kirk Schloegel, George Karypis, Vipin Kumar, J. Dongarra, I. Foster, G. Fox, ...

Contents 0.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 0.2 Modeling Mesh-based Computations as Graphs . . . . . . . . . . . . . . . ....

Analysis of Recommendation Algorithms for E-Commerce Badrul Sarwar, George Karypis, Joseph Konstan, and John Riedl (2000)

Grouplens Research Group, Badrul Sarwar, George Karypis, Joseph Konstan, John Riedl

AB;C:<=!?=>DE:<=>DE/F?AG?465IHJ41FKAE-F57L-M5DE:<N /91O-98P;Q=>-0/!R4D+SUT-0:=>1V=>R-@78>1WAE-02X1Y#2Z?HJDE4L[@78>1J5T/\=]8>-0/012QN...

Submitted to EuroPar 2000 Gang Scheduling for Distributed Memory Systems \Lambda (2000)

William Leinberger, George Karypis, Vipin Kumar

A unified algorithm for load-balancing adaptive scientific simulations (2000)

Multilevel k-way Hypergraph Partitioning (2000)

( kirk, karypis, kumar) @ cs.umn.edu

ANewAlgorithmforMulti-objectiveGraphPartitioning (1999)

In this paper, we present a new multilevel k-way hypergraph partitioning algorithm that substantially outperforms the existing state-of-the-art K-PM/LR algorithm for multi-way partitioning, both for...

Vipin Kumar, George Karypis, Kirk Schloegel

isthoseinwhichmultipleobjectives,eachofwhichcanbemodeledasasumofweightsoftheedgesofa thatthetraditionalgraphpartitioningmodelalonecannoteectivelyhandle.Onesuchclassofproblems...

Text Categorization Using Weight Adjusted k-Nearest Neighbor Classification (1999)

Euihong (sam Han, George Karypis, Vipin Kumar, Vipin Kumar

Categorization of documents is challenging, as the number of discriminating words can be very large. We present a nearest neighbor classification scheme for text categorization in which the...

Partitioning-based clustering for web document categorization. Decision Support Systems (1999)

Daniel Boley, Maria Gini, Robert Gross, Kyle Hastings, George Karypis, ...

Clustering techniques have been used by manyintelligent software agents in order to retrieve, lter, and categorize documents available on the World Wide Web. Clustering is also useful in extracting...

Multilevel refinement for hierarchical clustering (1999)

Text Categorization Using Weight Adjusted k-Nearest Neighbor Classification (1999)

A new algorithm for multi-objective graph partitioning (1999)

Abstract. Automatic text categorization is an important task that can help people finding information on huge online resources. Text categorization presents unique challenges due to the large number...

PSPASES: An efficient and scalable parallel sparse direct solver (1999)

( kirk, karypis, kumar) @ cs.umn.edu

Mahesh Joshi, George Karypis, Vipin Kumar, Anshul Gupta, Fred Gustavson

Many problems in engineering and scientific domains require solving large sparse systems of linear equations, as a computationally intensivesteptowards the final solution. It has long beenachallenge...

Partitioning-Based Clustering for Web Document Categorization (1999)

Daniel Boley Maria, Maria Gini, Robert Gross, Kyle Hastings, George Karypis, ...

Clustering techniques have been used by many intelligent software agents in order to retrieve, filter, and categorize documents available on the World Wide Web. Clustering is also useful in...

Partitioning-Based Clustering for Web Document Categorization (1999)

Daniel Boley Maria, Maria Gini, Robert Gross, Kyle Hastings, George Karypis, ...

Clustering techniques have been used by many intelligent software agents in order to retrieve, filter, and categorize documents available on the World Wide Web. Clustering is also useful in...

Parallel Multilevel Algorithms for Multi-Constraint Graph Partitioning (1999)

Kirk Schloegel And, Kirk Schloegel, George Karypis, Vipin Kumar

Recently, sequential multi-constraint graph partitioning algorithms have been developed to address the load balancing requirements of emerging multi-phase and multi-physics scientific simulation...

Partitioning-Based Clustering for Web Document Categorization (1999)

Daniel Boley Maria, Maria Gini, Robert Gross, Kyle Hastings, George Karypis, ...

Clustering techniques have been used by many intelligent software agents in order to retrieve, filter, and categorize documents available on the World Wide Web. Clustering is also useful in...

A Universal Formulation of Sequential Patterns (1999)

Mahesh Joshi, George Karypis, Vipin Kumar

This report outlines a more general formulation of sequential patterns, which uni#es the generalized patterns proposed by Srikant and Agarwal #SA96# and episode discovery approach taken by Manilla et...

CHAMELEON: A Hierarchical Clustering Algorithm Using Dynamic Modeling (1999)

George Karypis, Eui-Hong (Sam) Han, Vipin Kumar

Clustering in data mining is a discovery process that groups a set of data such that the intracluster similarity is maximized and the intercluster similarity is minimized. Existing clustering...

A New Algorithm for Multi-objective Graph Partitioning (1999)

Kirk Schloegel George, George Karypis, Vipin Kumar

Recently, a number of graph partitioning applications have emerged with additional requirements that the traditional graph partitioning model alone cannot effectively handle. One such class of...

Parallel Multilevel Algorithms for Multi-Constraint Graph Partitioning (1999)

Document Categorization and Query Generation on the World Wide Web Using WebACE (1999)

Recently, sequential multi-constraint graph partitioning algorithms have been developed to address the load balancing requirements of emerging multi-phase and multi-physics scientific simulation...

Daniel Boley, Maria Gini, Robert Gross, Eui-Hong (Sam) Han, Kyle Hastings, George Karypis, ...

We present WebACE, an agent for exploring and categorizing documents on the World Wide Web based on a user profile. The heart of the agent is an unsupervised categorization of a set of documents,...

Parallel Multilevel Algorithms for Multi-Constraint Graph Partitioning (1999)

Kirk Schloegel And, Kirk Schloegel, George Karypis, Vipin Kumar

Recently, sequential multi-constraint graph partitioning algorithms have been developed to address the load balancing requirements of emerging multi-phase and multi-physics scientific simulation...

Multilevel Algorithms for Multi-Constraint Hypergraph Partitioning (1999)

PSPASES: An Efficient and Scalable Parallel Sparse Direct Solver (1999)

Traditional hypergraph partitioning algorithms compute a bisection a graph such that the number of hyperedges that are cut by the partitioning is minimized and each partition has an equal number of...

Mahesh Joshi, George Karypis, Vipin Kumar, Anshul Gupta, Fred Gustavson

Many problems in engineering and scientific domains require solving large sparse systems of linear equations, as a computationally intensive step towards the final solution. It has long been a...

Multilevel Refinement for Hierarchical Clustering (1999)

George Karypis, Eui-hong (Sam) Han, Vipin Kumar

Hierarchical methods are well known clustering technique that can be potentially very useful for various data mining tasks. A hierarchical clustering scheme produces a sequence of clusterings in...

Multilevel Refinement for Hierarchical Clustering (1999)

George Karypis, Eui-Hong (Sam) Han, Vipin Kumar

Hierarchical methods are well known clustering technique that can be potentially very useful for various data mining tasks. A hierarchical clustering scheme produces a sequence of clusterings in...

Partitioning-Based Clustering for Web Document Categorization (1999)

Daniel Boley, Maria Gini, Robert Gross, Kyle Hastings, George Karypis, ...

Clustering techniques have been used by many intelligent software agents in order to retrieve, filter, and categorize documents available on the World Wide Web. Clustering is also useful in...

A Universal Formulation of Sequential Patterns (1999)

Mahesh Joshi, George Karypis, Vipin Kumar

This report outlines a more general formulation of sequential patterns, which unifies the generalized patterns proposed by Srikant and Agarwal [SA96] and episode discovery approach taken by Manilla...

CHAMELEON: A Hierarchical Clustering Algorithm Using Dynamic Modeling (1999)

George Karypis, Eui-Hong (Sam) Han, Vipin Kumar

Clustering in data mining is a discovery process that groups a set of data such that the intracluster similarity is maximized and the intercluster similarity is minimized. Existing clustering...

A Universal Formulation of Sequential Patterns (1999)

Mahesh Joshi George, George Karypis, Vipin Kumar

This report outlines a more general formulation of sequential patterns, which unifies the generalized patterns proposed by Srikant and Agarwal [SA96] and episode discovery approach taken by Manilla...

A New Algorithm for Multi-objective Graph Partitioning (1999)

A New Algorithm for Multi-objective Graph Partitioning (1999)

. Recently, a number of graph partitioning applications have emerged with additional requirements that the traditional graph partitioning model alone cannot effectively handle. One such class of...

Text Categorization Using Weight Adjusted k-Nearest Neighbor Classification (1999)

Recently, a number of graph partitioning applications have emerged with additional requirements that the traditional graph partitioning model alone cannot effectively handle. One such class of...

Document Categorization and Query Generation on the World Wide Web Using WebACE (1999)

Text categorization is the task of deciding whether a document belongs to a set of prespecified classes of documents. Automatic classification schemes can greatly facilitate the process of...

Daniel Boley Maria, Maria Gini, Robert Gross, Kyle Hastings, George Karypis, ...

We present WebACE, an agent for exploring and categorizing documents on the World Wide Web based on a user profile. The heart of the agent is an unsupervised categorization of a set of documents,...

Document Categorization and Query Generation on the World Wide Web Using WebACE (1999)

Daniel Boley, Maria Gini, Robert Gross, Kyle Hastings, George Karypis, ...

We present WebACE, an agent for exploring and categorizing documents on the World Wide Web based on a user profile. The heart of the agent is an unsupervised categorization of a set of documents,...

A new algorithm for multi-objective graph partitioning (1999)

Extended Abstract- Submitted to SC'99 Job Scheduling in the presence of Multiple Resource Requirements (1999)

( kirk, karypis, kumar) @ cs.umn.edu

William Leinberger, George Karypis, Vipin Kumar

In past massively parallel processing systems, such as the Intel Paragon and the CRI T3E, the scheduling problem consisted of allocating a single type of resource among the waiting jobs; the...

Macromolecule Mass Spectrometry: Citation Mining of User Documents (1998)

Kostoff, Ronald N., Bedford, Clifford D., Rio, Jesus A. Del, Cortes, Hector D., Karypis, George

Identifying research users, applications, and impact is important for research performers, managers, evaluators, and sponsors. It is important to know whether the audience reached is the audience...

Science and Technology Text Mining: Electric Power Sources (1998)

Kostoff, Ronald N., Tshiteya, Rene, Pfeil, Kirstin M., Humenik, James A., Karypis, George

Database Tomography (DT) is a textual database analysis system consisting of two major components: 1) algorithms for extracting multi-word phrase frequencies and phrase proximities (physical...

Science and Technology Text Mining: Wireless LANS (1998)

Kostoff, Ronald N., Tshiteya, Rene, Stump, Jesse, Malpohl, Guido, Karypis, George

Database Tomography (DT) is a textual database analysis system consisting of two major components: 1) algorithms for extracting multi-word phrase frequencies and phrase proximities (physical...

Finding Frequent Patterns in a Large Sparse Graph (1998)

BAMBOO: Accelerating Closed Itemset Mining by Deeply Pushing the Length-Decreasing Support Constraint (1998)

This paper presents two algorithms based on the horizontal and vertical pattern discovery paradigms that find the connected subgraphs that have a sufficient number of edge disjoint embeddings in a...

Wang, Jianyong, Karypis, George

Previous study has shown that mining frequent patterns with length-decreasing support constraint is very helpful in removing some uninteresting patterns based on the observation that short patterns...

SLPMiner: An Algorithm for Finding Frequent Sequential Patterns Using Length-Decreasing Support Constraint (1998)

Seno, Masakazu, Karypis, George

Over the years, a variety of algorithms for finding frequent sequential patterns in very large sequential databases have been developed. The key feature in most of these algorithms is that they use a...

Discovering Frequent Geometric Subgraphs (1998)

Selective Markov Models for Predicting Web-Page Accesses (1998)

As data mining techniques are being increasingly applied to non-traditional domains, existing approaches for finding frequent itemsets cannot be used as they cannot model the requirement of these...

Deshpande, Mukund, Karypis, George

The problem of predicting a user's behavior on a web-site has gained importance due to the rapid growth of the world-wide-web and the need to personalize and influence a user's browsing experience....

Using Conjunction of Attribute Values for Classification (1998)

Deshpande, Mukund, Karypis, George

Abstract Advances in the efficient discovery of frequent itemsets in large databases have led to the development of a number of schemes that use frequent itemsets to aid in the development of...

Multilevel Algorithms for Partitioning Power-Law Graphs (1998)

Abou-rjeili, Amine, Karypis, George

Graph partitioning is an enabling technology for parallel processing as it allows for the effective decomposition of unstructured computations whose data dependencies correspond to a large sparse and...

Efficient Closed Pattern Mining in the Presence of Tough Block Constraints (1998)

Gade, Krishna, Wang, Jianyong, Karypis, George

In recent years, various constrained frequent pattern mining problem formulations and associated algorithms have been developed that enable the user to specify various itemset based constraints that...

THETO - A Fast and High-Quality Partitioning Driven Global Placer (1998)

Selvakkumaran, Navaratnasothie, Karypis, George

Partitioning driven placement approaches are often preferred for fast and scalable solutions to large placement problems. However, due to the inaccuracy of representing wirelength objective by cut...

Partitioning Algorithms for Simultaneously Balancing Iterative and Direct Methods (1998)

Moulitsas, Irene, Karypis, George

This paper focuses on domain decomposition-based numerical simulations whose sub problems corresponding to the various subdomains are solved using sparse direct factorization methods (e.g., FETI)....

Soft Clustering Criterion Functions for Partitional Document Clustering (1998)

GREWA Scalable Frequent Subgraph Discovery Algorithm (1998)

Recently published studies have shown that partitional clustering algorithms that optimize certain criterion functions, which measure key aspects of inter- and intra-cluster similarity, are very...

SUMMARY: Efficiently Summarizing Transactions for Clustering (1998)

Existing algorithms that mine graph datasets to discover patterns corresponding to frequently occurring subgraphs can operate efficiently on graphs that are sparse, contain a large number of...

Wang, Jianyong, Karypis, George

Frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. In recent years, several studies have also extended its application to the...

Finding Functionally Related Genes by Local and Global Analysis of MEDLINE Abstracts (1998)

Nakken, Sigve, Kauffman, Christopher, Karypis, George

Discovery of biological relationships between genes is one of the keys to understanding the complex functional nature of the human genome. Currently, most of the knowledge about interrelating genes...

HARMONY: Efficiently Mining the Best Rules for Classification (1998)

Wang, Jianyong, Karypis, George

Many studies have shown that rule-based classification algorithms perform well in classifying categorical and sparse high-dimensional databases. However, a fundamental limitation with many rule-based...

Multi-Objective Hypergraph Partitioning Algorithms for Cut and Maximum Subdomain Degree Minimization (1998)

Selvakkumaran, Navaratnasothie, Karypis, George

In this paper we present a family of multi-objective hypergraph partitioning algorithms based on the multilevel paradigm, which are capable of producing solutions in which both the cut and the...

Scalable Partitioning Algorithms for FPGAs With Heterogeneous Resources (1998)

Selvakkumaran, Navaratnasothie, Ranjan, Abhishek, Raje, Salil, Karypis, George

As FPGA densities increase, partitioning-based FPGA placement approaches are becoming increasingly important as they can be used to provide high-quality and computationally scalable placement...

Discovering Frequent Geometric Subgraphs (1998)

Profile Based Direct Kernels for Remote Homology Detection and Fold Recognition (1998)

Data mining-based analysis methods are increasingly being applied to datasets derived from science and engineering domains that model various physical phenomena and objects. In many of these...

An Efficient Algorithm for Discovering Frequent Subgraphs (1998)

Remote homology detection between protein sequences is a central problem in computational biology. Supervised learning algorithms based on support vector machines are currently the most effective...

Automated Approaches for Classifying Structures (1998)

Over the years, frequent itemset discovery algorithms have been used to find interesting patterns in various application areas. However, as data mining techniques are being increasingly applied to...

Deshpande, Mukund, Kuramochi, Michihiro, Karypis, George

In this paper we study the problem of classifying chemical compound datasets. We present an algorithm that first mines the chemical compound dataset to discover discriminating sub-structures; these...

Prediction of Contact Maps Using Support Vector Machines (1998)

Comparison of Agglomerative and Partitional Document Clustering Algorithms (1998)

Contact map prediction is of great interests for its application in fold recognition and protein 3D structure determination. In particular, we focusd on predicting non-local interactions in this...

CLUTO - A Clustering Toolkit (1998)

Fast and high-quality document clustering algorithms play an important role in providing intuitive navigation and browsing mechanisms by organizing large amounts of information into a small number of...

Concept Indexing: A Fast Dimensionality Reduction Algorithm With Applications to Document Retrieval and Categorization (1998)

Clustering algorithms divide data into meaningful or useful groups, called clusters, such that the intra-cluster similarity is maximized and the inter-cluster similarity is minimized. These...

Karypis, George, Han, Euihong

In recent years, we have seen a tremendous growth in the volume of text documents available on the Internet, digital libraries, news sources, and company-wide intranets. This has led to an increased...

Centroid-Based Document Classification Algorithms: Analysis & Experimental Results (1998)

Han, Euihong, Karypis, George

In recent years we have seen a tremendous growth in the volume of text documents available on the Internet, digital libraries, news sources, and company-wide intranets. Automatic text categorization,...

Application of Dimensionality Reduction in Recommender System - A Case Study (1998)

Sarwar, Badrul, Karypis, George, Konstan, Joseph, Riedl, John

We investigate the use of dimensionality reduction to improve performance for a new class of data analysis software called "recommender systems" Recommender systems apply knowledge discovery...

Evaluation of Item-Based Top-N Recommendation Algorithms (1998)

Efficient Algorithms for Creating Product Catalogs (1998)

The explosive growth of the world-wide-web and the emergence of e-commerce has led to the development of recommender systems a personalized information filtering technology used to identify a set of...

Steinbach, Michael, Karypis, George, Kumar, Vipin

For the purposes of this paper we define a catalog to be a promotional catalog, i.e., a collection of products (items) presented to a customer with the hope of encouraging a purchase. The single...

Evaluation of Hierarchical Clustering Algorithms for Document Datasets (1998)

Load Balancing Across Near-Homogeneous Multi-Resource Servers (1998)

Fast and high-quality document clustering algorithms play an important role in providing intuitive navigation and browsing mechanisms by organizing large amounts of information into a small number of...

Lienberger, William, Karypis, George, Kumar, Vipin, Biswas, Rupak

An emerging model for computational grids interconnects similar multi-resource servers from distributed sites. A job submitted to the grid can be executed by any of the servers; however, resource...

PAFI: A Pattern Finding Toolkit (1998)

Seno, Masakazu, Kuramochi, Michihiro, Karypis, George

PAFI is a set of programs that can be used to find frequent patterns in large and diverse databases. The current release of PAFI includes three different pattern discovery programs called LPMiner,...

Multi-Constraint Mesh Partitioning for Contact/Impact Computations (1998)

Multi-Objective Hypergraph Partitioning Algorithms for Cut and Maximum Subdomain Degree Minimization (1998)

We present a novel approach for decomposing contact/impact computations in which the mesh elements come in contact with each other during the course of the simulation. Effective decomposition of...

Selvakkumaran, Navaratnasothie, Karypis, George

In this paper we present a family of multi-objective hypergraph partitioning algorithms based on the multilevel paradigm, which are capable of producing solutions in which both the cut and the...

Frequent Sub-Structure-Based Approaches for Classifying Chemical Compounds (1998)

Deshpande, Mukund, Kuramochi, Michihiro, Karypis, George

In this paper we study the problem of classifying chemical compound datasets. We present a sub-structure-based classification algorithm that decouples the sub-structure discovery process from the...

Finding Frequent Patterns Using Length-Decreasing Support Constraints (1998)

Seno, Masakazu, Karypis, George

Finding prevalent patterns in large amount of data has been one of the major problems in the area of data mining. Particularly, the problem of finding frequent itemset or sequential patterns in very...

Parallel Formulations of Tree-Projection Based Sequence Mining Algorithms (1998)

Guralnik, Valerie, Karypis, George

Discovery of sequential patterns is becoming increasingly useful and essential in many scientific and commercial domains. Enormous sizes of available datasets and possibly large number of mined...

Better Kernels and Coding Schemes Lead to Improvements in SVM-Based Secondary Structure Prediction (1998)

Improve Precategorized Collection Retrieval by Using Supervised Term Weighting Schemes (1998)

The accurate prediction of a protein's secondary structure plays an increasingly critical role in predicting its function and tertiary structure, as it is utilized by many of the current...

Weight Adjustment Schemes for a Centroid Based Classifier (1998)

The emergence of the world-wide-web has led to an increased interest in methods for searching for information. A key characteristic of many of the online document collections is that the documents...

Shankar, Shrikanth, Karypis, George

In recent years we have seen a tremendous growth in the volume of text documents available on the Internet, digital libraries, news sources, and company-wide intra-nets. Automatic text...

Text Categorization Using Weight Adjusted k-Nearest Neighbor Classification (1998)

Han, Euihong, Karypis, George, Kumar, Vipin

Categorization of documents is challenging, as the number of discriminating words can be very large. The authors present a nearest neighbor classification scheme for text categorization in which the...

Multilevel Refinement for Hierarchical Clustering (1998)

Karypis, George, Han, Euihong, Kumar, Vipin

Hierarchical methods are well-known clustering techniques that can be potentially very useful for various data mining tasks. A hierarchical clustering scheme produces a sequence of clusterings in...

Multilevel Algorithms for Multi-Constraint Hypergraph Partitioning (1998)

Average Positive of User Clicks as an Automated and Not-Intrusive Way of Evaluating Ranking Methods (1998)

Traditional hypergraph partitioning algorithms compute a bisection of a graph such that the number of hyperedges that are cut by the partitioning is minimized and each partition has an equal number...

Oztekin, B., Karypis, George, Kumar, Vipin

The need for an objective and automated way of evaluating the performance of different ranking/ methods is becoming increasingly important in the web search domain. There are various methods for...

Item-Based Top-N Recommendation Algorithms (1998)

Deshpande, Mukund, Karypis, George

The explosive growth of the world-wide-web and the emergence of e-commerce has led to the development of recommender systems a personalized information filtering technology used to identify a set of...

Architecture Aware Partitioning Algorithms (1998)

Moulitsas, Irene, Karypis, George

Existing partitioning algorithms provide limited support for load balancing simulations that are performed on heterogeneous parallel computing platforms. On such architectures, effective load...

Protein Structure Prediction Using String Kernels (1998)

Rangwala, Huzefa, DeRonne, Kevin, Karypis, George

With recent advances in large-scale sequencing technologies, there has been an exponential growth in protein sequence information. Currently, the ability to produce sequence information far out-paces...

Effective Optimization Algorithms for Fragment-Assembly Based Protein Structure Prediction (1998)

DeRonne, Kevin W., Karypis, George

Despite recent developments in protein structure prediction, an accurate new fold prediction algorithm remains elusive. One of the challenges facing current techniques is the size and complexity of...

Acyclic Subgraph Based Descriptor Spaces for Chemical Compound Retrieval and Classification (1998)

Wale, Nikil, Karypis, George

In recent years the development of computational techniques that build models to correctly assign chemical compounds to various classes or to retrieve potential drug-like compounds has been an active...

Incremental Window-based Protein Sequence Alignment Algorithms (1998)

Building Multiclass Classifiers for Remote Homology Detection and Fold Recognition (1998)

MOTIVATION: Protein sequence alignment plays a critical role in computational biology as it is an integral part in many analysis tasks designed to solve problems in comparative genomics, structure...

A fast and high quality multilevel scheme for partitioning irregular graphs (1998)

Protein remote homology prediction and fold recognition are central problems in computational biology. Supervised learning algorithms based on support vector machines are currently one of the most...

Multilevel algorithms for multi-constraint graph partitioning (1998)

Abstract. Recently, a number of researchers have investigated a class of graph partitioning algorithms that reduce the size of the graph by collapsing vertices and edges, partition the smaller graph,...

Multilevel algorithms for multi-constraint graph partitioning (1998)

( kirk, karypis, kumar) @ cs.umn.edu

A parallel algorithm for multilevel graph partitioning and sparse matrix ordering (1998)

Traditional graph partitioning algorithms compute a k-way partitioning of a graph such that the number of edges that are cut by the partitioning is minimized and each partition has an equal number of...

Multilevel k-way partitioning scheme for irregular graphs (1998)

In this paper we present a parallel formulation of the multilevel graph partitioning and sparse matrix ordering algorithm. A key feature of our parallel formulation (that distinguishes it from other...

Multilevel k-way partitioning scheme for irregular graphs (1998)

In this paper we present and study a class of graph partitioning algorithms that reduce the size of the graph by collapsing vertices and edges, find a k-way partitioning of the smaller graph, and...

A fast and high quality multilevel scheme for partitioning irregular graphs (1998)

In this paper we present a parallel formulation of a multilevel k-way graph partitioning algorithm. The multilevel k-way partitioning algorithm reduces the size of the graph by collapsing vertices...

Multilevel algorithms for multi-constraint graph partitioning (1998)

Recently, a number of researchers have investigated a class of graph partitioning algorithms that reduce the size of the graph by collapsing vertices and edges, partition the smaller graph, and then...

A fast and high quality multilevel scheme for partitioning irregular graphs (1998)

Sequential multi-constraint graph partitioning algorithms havebeendeveloped to address the load balancing requirements of multi-phase simulations. The efficient execution of large multi-phase...

Appears in the Journal of Parallel and Distributed Computing (1998)

Recently, a number of researchers have investigated a class of graph partitioning algorithms that reduce the size of the graph by collapsing vertices and edges, partition the smaller graph, and then...

Short Version Of, George Karypis, Vipin Kumar

In this paper we present a parallel formulation of the multilevel graph partitioning and sparse matrix ordering algorithm. A key feature of our parallel formulation (that distinguishes it from other...

ScalParC: A New Scalable and Efficient Parallel Classification Algorithm for Mining Large Datasets (1998)

ScalParC : A New Scalable and Efficient Parallel Classification Algorithm for Mining Large Datasets (1998)

In this paper, we present ScalParC (Scalable Parallel Classifier), a new parallel formulation of a decision tree based classification process. Like other state-of-the-art decision tree classifiers...

Mahesh Joshi George, George Karypis

In this paper, we present ScalParC (Scalable Parallel Classifier), a new parallel formulation of a decision tree based classification process. Like other state-of-the-art decision tree classifiers...

A fast and high quality multilevel scheme for partitioning irregular graphs (1998)

ScalParC: A New Scalable and Efficient Parallel Classification Algorithm for Mining Large Datasets (1998)

Recently, a number of researchers have investigated a class of graph partitioning algorithms that reduce the size of the graph by collapsing vertices and edges, partition the smaller graph, and then...

SUMMARY: Efficiently Summarizing Transactions for Clustering (1998)

In this paper, we present ScalParC #Scalable Parallel Classi#er#, a new parallel formulation of a decision tree based classi#cation process. Like other state-of-the-art decision tree classi#ers such...

J. Wang, Jianyong Wang, Jianyong Wang, G. Karypis, George Karypis

Frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. In recent years, several studies have also extended its application to the...

Multilevel k-way partitioning scheme for irregular graphs (1998)

Wavefront Diffusion and LMSR: Algorithms for Dynamic Repartitioning of Adaptive Meshes (1998)

In this paper we present and study a class of graph partitioning algorithms that reduce the size of the graph by collapsing vertices and edges, find a k-way partitioning of the smaller graph, and...

Wavefront Diffusion and LMSR: Algorithms for Dynamic Repartitioning of Adaptive Meshes (1998)

Existing state-of-the-art schemes for dynamic repartitioning of adaptive meshes can be classified as either diffusion-based schemes or scratch-remap schemes. We present a new scratch-remap scheme...

September 20, 1998 (1998)

Existing state-of-the-art schemes for dynamic repartitioning of adaptive meshes can be classi#ed as either di#usion-based schemes or scratch-remap schemes. We present a new scratch-remap scheme...

Metis Mee Tis, George Karypis, Vipin Kumar

Contents 1 Introduction 3 2 What is METIS 4 3 What is New in This Version 6 4 METIS's Stand-Alone Programs 8 4.1 Graph Partitioning Programs . . . . . . . . . . . . . . . . . . . . . . . . . . ....

Wavefront Diffusion and LMSR: Algorithms for Dynamic Repartitioning of Adaptive Meshes (1998)

ScalParC: A New Scalable and Efficient Parallel Classification Algorithm for Mining Large Datasets (1998)

Existing state-of-the-art schemes for dynamic repartitioning of adaptive meshes can be classified as either diffusion-based schemes or scratch-remap schemes. We present a new scratch-remap scheme...

WebACE: A Web Agent for Document Categorization and Exploration (1998)

In this paper, we present ScalParC (Scalable Parallel Classifier), a new parallel formulation of a decision tree based classification process. Like other state-of-the-art decision tree classifiers...

Eui-Hong Han, Daniel Boley, Maria Gini, Robert Gross, Kyle Hastings, ...

We propose an agent for exploring and categorizing documents on the World Wide Web based on a user profile. The heart of the agent is an automatic categorization of a set of documents, combined with...

Hypergraph Based Clustering in High-Dimensional Data Sets: A Summary of Results (1998)

Eui-Hong (Sam) Han, George Karypis, Vipin Kumar, Bamshad Mobasher

Clustering of data in a large dimension space is of a great interest in many data mining applications. In this paper, we propose a method for clustering of data in a high dimensional space based on a...

WebACE: A Web Agent for Document Categorization and Exploration (1998)

Daniel Boley, Maria Gini, Robert Gross, Kyle Hastings, George Karypis, ...

We propose an agent for exploring and categorizing documents on the World Wide Web based on a user pro#le. The heart of the agent is an automatic categorization of a set of documents, combined with a...

A Fast And High Quality Multilevel Scheme For Partitioning Irregular Graphs (1998)

Multilevel k-way Hypergraph Partitioning (1998)

.<F3.819e+05> Recently, a number of researchers have investigated a class of graph partitioning algorithms that reduce the size of the graph by collapsing vertices and edges, partition the...

Multilevel algorithms for multi-constraint graph partitioning (1998)

In this paper, we present a new multilevel k-way hypergraph partitioning algorithm that substantially outperforms the existing state-of-the-art K-PM/LR algorithm for multi-way partitioning. both for...

Multilevel algorithms for multi-constraint graph partitioning (1998)

Sequential multi-constraint graph partitioning algorithms have beendeveloped to address the load balancing requirements of multi-phase simulations. The e cient execution of large multi-phase...

Scalable Parallel Algorithms for Sparse Linear Systems, (1997)

Traditional hypergraph partitioning algorithms compute a bisection a graph such that the number of hyperedges that are cut by the partitioning is minimized and each partition has an equal number of...

Gupta, Anshul, Karypis, George, Kumar, Vipin

Large sparse linear systems occur in many scientific and engineering applications encountered in military and civilian domains. Such systems are typically solved using either iterative or direct...

Multilevel hypergraph partitioning: Application in VLSI domain (1997)

George Karypis, Rajat Aggarwal, Vipin Kumar, Senior Member, Shashi Shekhar, Senior Member

Abstract — In this paper, we present a new hypergraphpartitioning algorithm that is based on the multilevel paradigm. In the multilevel paradigm, a sequence of successively coarser hypergraphs is...

Multilevel hypergraph partitioning: Application in VLSI domain (1997)

George Karypis, Rajat Aggarwal, Vipin Kumar, Shashi Shekhar

In this paper, we present a new hypergraph partitioning algorithm that is based on the multilevel paradigm. In the multilevel paradigm, a sequence of successively coarser hypergraphs is constructed....

Web page categorization and feature selection using association rule and principal component clustering (1997)

Jerome Moore, Daniel Boley, Maria Gini, Robert Gross, Kyle Hastings, ...

Clustering techniques have been used by many intelligent software agents in order to retrieve, filter, and categorize documents available on the World Wide Web. Clustering is also useful in...

A Coarse-Grain Parallel Formulation of Multilevel k-way Graph Partitioning Algorithm (1997)

Multilevel hypergraph partitioning: Application in VLSI domain (1997)

In this paper we present a parallel formulation of a multilevel k-way graph partitioning algorithm, that is particularly suited for message-passing libraries that have high latency. The multilevel...

George Karypis, Rajat Aggarwal, Vipin Kumar, Shashi Shekhar

In this paper, we present a new hypergraph partitioning algorithm that is based on the multilevel paradigm. In the multilevel paradigm, a sequence of successively coarser hypergraphs is constructed....

A High Performance Two Dimensional Scalable Parallel Algorithm for Solving Sparse Triangular Systems (1997)

Mahesh Joshi Anshul, Mahesh V. Joshi, Anshul Gupta, George Karypis

Solving a system of equations of the form Tx = y, where T is a sparse triangular matrix, is required after the factorization phase in the direct methods of solving systems of linear equations. A few...

Design and Implementation of a Scalable Parallel Direct Solver for Sparse Symmetric Positive Definite Systems: Preliminary Results (1997)

Anshul Gupta, Fred Gustavson, Mahesh Joshi, George Karypis, Vipin Kumar

Solving large sparse systems of linear equations is at the core of many problems in engineering and scientific computing. It has long been a challenge to develop parallel formulations of sparse...

Multilevel Diffusion Schemes for Repartitioning of Adaptive Meshes (1997)

Kirk Schloegel George, George Karypis, Vipin Kumar

For a large class of irregular mesh applications, the structure of the mesh changes from one phase of the computation to the next. Eventually, as the mesh evolves, the adapted mesh has to be...

Web Page Categorization and Feature Selection Using Association Rule and Principal Component Clustering (1997)

Jerome Moore, Eui-Hong Han, Daniel Boley, Maria Gini, Robert Gross, ...

Clustering techniques have been used by many intelligent software agents in order to retrieve, filter, and categorize documents available on the World Wide Web. Clustering is also useful in...

Appears in the (1997)

Th Siam Conference, George Karypis, Vipin Kumar

In this paper we present a parallel formulation of a multilevel k-way graph partitioning algorithm, that is particularly suited for message-passing libraries that have high latency. The multilevel...

Multilevel Diffusion Schemes for Repartitioning of Adaptive Meshes (1997)

Multilevel Diffusion Schemes for Repartitioning of Adaptive Meshes (1997)

For a large class of irregular grid applications, the structure of the mesh changes from one phase of the computation to the next. Eventually, as the graph evolves, the adapted mesh has to be...

Min-Apriori: An Algorithm for Finding Association Rules in Data with Continuous Attributes (1997)

For a large class of irregular grid applications, the structure of the mesh changes from one phase of the computation to the next. Eventually, as the graph evolves, the adapted mesh has to be...

A Coarse-Grain Parallel Formulation of Multilevel . . . (1997)

this paper, we propose a new algorithm to discover association rules in the type of data set discussed in the above paragraph.

Parallel Multilevel Diffusion Algorithms for Repartitioning of Adaptive Meshes (1997)

In this paper we present a parallel formulation of a multilevel k-way graph partitioning algorithm, that is particularly suited for high latency message-passing libraries. The multilevel k-way...

Multilevel Diffusion Schemes for Repartitioning of Adaptive Meshes (1997)

Graph partitioning has been shown to be an effective way to divide a large computation over an arbitrary number of processors. A good partitioning can ensure load balance and minimize the...

Kirk Schloegel George, George Karypis, Vipin Kumar

For a large class of irregular grid applications, the structure of the mesh changes from one phase of the computation to the next. Eventually, as the graph evolves, the adapted mesh has to be...

Scalable Parallel Data Mining for Association Rules (1997)

Web Page Categorization and Feature Selection Using Association Rule and Principal Component Clustering (1997)

One of the important problems in data mining is discovering association rules from databases of transactions where each transaction consists of a set of items. The most time consuming operation in...

Jerome Moore, Daniel Boley, Maria Gini, Robert Gross, Kyle Hastings, ...

Clustering techniques have been used by manyintelligent software agents in order to retrieve, #lter, and categorize documents available on the World Wide Web. Clustering is also useful in extracting...

Web Page Categorization and Feature Selection Using Association Rule and Principal Component Clustering (1997)

Jerome Moore, Eui-Hong (Sam) Han, Daniel Boley, Maria Gini, Robert Gross, Kyle Hastings, ...

Clustering techniques have been used by many intelligent software agents in order to retrieve, filter, and categorize documents available on the World Wide Web. Clustering is also useful in...

A High Performance Two Dimensional Scalable Parallel Algorithm for Solving Sparse Triangular Systems (1997)

Mahesh Joshi, Anshul Gupta, George Karypis

Solving a system of equations of the form Tx = y, where T is a sparse triangular matrix, is required after the factorization phase in the direct methods of solving systems of linear equations. A few...

Scalable Parallel Data Mining for Association Rules (1997)

Multilevel hypergraph partitioning: Application in VLSI domain (1997)

In this paper we propose two new parallel formulations of the Apriori algorithm that is used for computing association rules. These new formulations, IDD and HD, address the shortcomings of two...

George Karypis, Rajat Aggarwal, Vipin Kumar, Shashi Shekhar

Multilevel hypergraph partitioning: Application in VLSI domain (1997)

George Karypis, Rajat Aggarwal, Vipin Kumar, Shashi Shekhar

In this paper, we present a new hypergraph partitioning algorithm that is based on the multilevel paradigm. In the multilevel paradigm, a sequence of successively coarser hypergraphs is constructed....

Graph partitioning and its applications to scientific computing /--by George Karypis. (1996)

Karypis, George.

Thesis (Ph. D.)--University of Minnesota, 1996.

Parallel Threshold-based ILU Factorization (1996)

Parallel Threshold-based ILU Factorization (1996)

Factorization algorithms based on threshold incomplete LU factorization have been found to be quite effective in preconditioning iterative system solvers. However, their parallel formulations have...

Analysis of multilevel graph partitioning (1995)

this paper we show that highly parallel graph partitioning algorithms in conjunction with parallel algorithms for computing maximal independent sets can be used to develop scalable parallel...

Analysis of multilevel graph partitioning (1995)

Recently, a number of researchers have investigated a class of algorithms that are based on multilevel graph partitioning that have moderate computational complexity, and provide excellent graph...

METIS - Unstructured Graph Partitioning and Sparse Matrix Ordering System, Version 2.0 (1995)

Permission to make digital or hard copies of part or all of this work or personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial...

Highly Scalable Parallel Algorithms for Sparse Matrix Factorization (1995)

this paper is organized as follows: Section 2 briefly describes the various ideas and algorithms implemented in METIS. Section 3 describes the user interface to the METIS graph partitioning and...

Parallel Multilevel Graph Partitioning (1995)

In this paper, we describe scalable parallel algorithms for sparse matrix factorization, analyze their performance and scalability, and present experimental results for up to 1024 processors on a...

Multilevel Graph Partitioning Schemes (1995)

In this paper we present a parallel formulation of a graph partitioning and sparse matrix ordering algorithm that is based on a multilevel algorithm we developed recently. Our parallel algorithm...

Analysis of multilevel graph partitioning (1995)

Abstract – In this paper we present experiments with a class of graph partitioning algorithms that reduce the size of the graph by collapsing vertices and edges, partition the smaller graph, and...

A high performance sparse Cholesky factorization algorithm for scalable parallel computers (1994)

In this paper we present a parallel formulation of a graph partitioning and sparse matrix ordering algorithm that is based on a multilevel algorithm we developed recently. Our parallel algorithm...

Performance and Scalability of the Parallel Simplex Method for Dense Linear Programming Problems An Extended Abstract (1994)

Abstract This paper presents a new parallel algorithm for sparse matrix factorization. This algorithm uses subforest-to-subcube mapping instead of the subtree-to-subcube mapping of another recently...

Highly scalable parallel algorithms for sparse matrix factorization (1994)

1 Introduction Linear programming is of fundamental importance in many optimization problems. The simplex method [4] is a commonly used way of solving linear programming problems. Solving large...

Highly scalable parallel algorithms for sparse matrix factorization (1994)

In this paper, we describe a scalable parallel algorithm for sparse matrix factorization, analyze their performance and scalability, and present experimental results for up to 1024 processors on a...

Highly scalable parallel algorithms for sparse matrix factorization (1994)

In this paper, we describe a scalable parallel algorithm for sparse matrix factorization, analyze their performance and scalability, and present experimental results for up to 1024 processors on a...

Performance and Scalability of the Parallel Simplex Method for Dense Linear Programming Problems (Extended Abstract) (1994)

In this paper, we describe scalable parallel algorithms for sparse matrix factorization, analyze their performance and scalability, and present experimental results for up to 1024 processors on a...

A High Performance Sparse Cholesky Factorization Algorithm For Scalable Parallel Computers (1994)

George Karypis and Vipin Kumar Computer Science Department University of Minnesota May 21, 1994 1 Introduction Linear programming is of fundamental importance in many optimization problems. The...

A High Performance Sparse Cholesky Factorization Algorithm For Scalable Parallel Computers (1994)

This paper presents a new parallel algorithm for sparse matrix factorization. This algorithm uses subforest-to-subcube mapping instead of the subtree-to-subcubemapping of another recently...

A High Performance Sparse Cholesky Factorization Algorithm for Scalable Parallel Computers (1994)

This paper presents a new parallel algorithm for sparse matrix factorization. This algorithm uses subforest-to-subcube mapping instead of the subtree-to-subcube mapping of another recently introduced...

Unstructured Tree Search on SIMD Parallel Computers (1994)

This paper presents a new parallel algorithm for sparse matrix factorization. This algorithm uses subforest-to-subcube mapping instead of the subtree-to-subcube mapping of another recently introduced...

A Parallel Formulation of Interior Point Algorithms (1994)

In this paper, we present new methods for load balancing of unstructured tree computations on large-scale SIMD machines, and analyze the scalability of these and other existing schemes. An efficient...

George Karypis, Anshul Gupta, Vipin Kumar

In recent years, interior point algorithms have been used successfully for solving mediumto large-size linear programming (LP) problems. In this paper we describe a highly parallel formulation of the...

A Parallel Formulation of Interior Point (1994)

Algorithms George Karypis, George Karypis, Anshul Gupta, Vipin Kumar

In recentyears, interior point algorithms have been used successfully for solving mediumto large-size linear programming #LP# problems. In this paper we describe a highly parallel formulation of the...

Efficient Parallel Formulations for Some Dynamic Programming Algorithms (1993)

Clustering In A High-Dimensional Space Using Hypergraph Models (1987)

In this paper we are concerned with Dynamic Programming (DP) algorithms whose solution is given by a recurrence relation similar to that for the matrix parenthesization problem. Guibas, Kung and...

Eui-Hong (Sam) Han, George Karypis, Vipin Kumar, Bamshad Mobasher

Clustering of data in a large dimension space is of a great interest in many data mining applications. Most of the traditional algorithms such as K-means or AutoClass fail to produce meaningful...

Interferon-inducible gene expression signature in peripheral blood cells of patients with severe lupus

Baechler, Emily C., Batliwalla, Franak M., Karypis, George, Gaffney, Patrick M., Ortmann, Ward A., Espe, Karl J., ...

Systemic lupus erythematosus (SLE) is a complex, inflammatory autoimmune disease that affects multiple organ systems. We used global gene expression profiling of peripheral blood mononuclear cells to...

wCLUTO: A Web-Enabled Clustering Toolkit1

Rasmussen, Matthew D., Deshpande, Mukund S., Karypis, George, Johnson, James, Crow, John A., Retzel, Ernest F.

As structural and functional genomics efforts provide the biological community with ever-broadening sets of interrelated data, the need to explore such complex information for subtle relationships...

Building multiclass classifiers for remote homology detection and fold recognition

Interferon-inducible gene expression signature in peripheral blood cells of patients with severe lupus

Baechler, Emily C., Batliwalla, Franak M., Karypis, George, Gaffney, Patrick M., Ortmann, Ward A., Espe, Karl J., ...

Systemic lupus erythematosus (SLE) is a complex, inflammatory autoimmune disease that affects multiple organ systems. We used global gene expression profiling of peripheral blood mononuclear cells to...

wCLUTO: A Web-Enabled Clustering Toolkit1

Rasmussen, Matthew D., Deshpande, Mukund S., Karypis, George, Johnson, James, Crow, John A., Retzel, Ernest F.

As structural and functional genomics efforts provide the biological community with ever-broadening sets of interrelated data, the need to explore such complex information for subtle relationships...

Building multiclass classifiers for remote homology detection and fold recognition