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...
Ananth Grama, Anshul Gupta, Eui-hong Han
The projected design space of petaFLOPS architectures entails exploitation of very large degrees of concurrency, locality of data access, and tolerance to latency. This puts considerable pressure on...
Personalized profile based search interface with ranked and clustered display (2001)
Sachin Kumar, B. Uygar Oztekin, Levent Ertoz, Saurabh Singhal, Euihong (sam Han, Vipin Kumar, ...
We have developed an experimental meta-search engine, which takes the snippets from traditional search engines and presents them to the user either in the form of clusters, indices or re-ranked list...
Centroid-Based Document Classification: Analysis & Experimental Results (2000)
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,...
Parallel Algorithms in Data Mining (2000)
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...
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...
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...
Document Categorization and Query Generation on the World Wide Web Using WebACE (1999)
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,...
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...
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...
Text Categorization Using Weight Adjusted k-Nearest Neighbor Classification (1999)
Eui-Hong (Sam) Han, George Karypis, Vipin Kumar
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...
Parallel Formulations of Decision-Tree Classification Algorithms (1998)
Anurag Srivastava, Eui-hong Han, Vineet Singh
. Classification decision tree algorithms are used extensively for data mining in many domains such as retail target marketing, fraud detection, etc. Highly parallel algorithms for constructing...
WebACE: A Web Agent for Document Categorization and Exploration (1998)
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...
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...
Min-Apriori: An Algorithm for Finding Association Rules in Data with Continuous Attributes (1997)
Eui-Hong (Sam) Han, George Karypis, Vipin Kumar
this paper, we propose a new algorithm to discover association rules in the type of data set discussed in the above paragraph.
Scalable Parallel Data Mining for Association Rules (1997)
Eui-Hong (Sam) Han, George Karypis, Vipin Kumar
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, 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...
Scalable Parallel Data Mining for Association Rules (1997)
Eui-Hong (Sam) Han, George Karypis, Vipin Kumar
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...
Parallel Formulations of Inductive Classification Learning Algorithm (1996)
Eui-Hong (Sam) Han, Anurag Srivastava, Vipin Kumar
One of the important problems in data mining [SAD + 93] is the classification--rule learning. The classification--rule learning involves finding rules or decision trees that partition given data into...
Visual Data Mining: Framework and Algorithm Development (1996)
M. Ganesh, Eui-Hong (Sam) Han, Vipin Kumar, Shashi Shekhar, Jaideep Srivastava
Visual data mining is the use of visualization techniques to allow data miners and analysts to evaluate, monitor, and guide the inputs, products and process of data mining. It can help introduce user...
Search Framework for Mining Classification Decision Trees (1996)
Eui-Hong (Sam) Han, Shashi Shekhar, Vipin Kumar, M. Ganesh, Jaideep Srivastava
Classification-rule-learning task is presented as a search process of finding a classification-decision tree that meets users' preferences and requirements. Users can control the efficiency of...
Web Mining: Pattern Discovery from World Wide Web Transactions (1996)
Bamshad Mobasher, Namit Jain, Eui-Hong (Sam) Han, Jaideep Srivastava
Web-based organizations often generate and collect large volumes of data in their daily operations. Analyzing such data can help these organizations to determine the life time value of clients,...
Clustering In A High-Dimensional Space Using Hypergraph Models (1987)
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...
Efficient Parallel Algorithms for Mining Associations
Mahesh V. Joshi, Eui-Hong (Sam) Han, George Karypis, Vipin Kumar
. 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,...
Efficient Parallel Algorithms for Mining Associations
Mahesh V. Joshi, Eui-Hong (Sam) Han, George Karypis, Vipin Kumar
. 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,...
Clustering Based On Association Rule Hypergraphs
Eui-Hong (Sam) Han, George Karypis, Bamshad Mobasher
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. These discovered clusters...
Clustering Based On Association Rule Hypergraphs
Eui-Hong (Sam) Han, George Karypis, Vipin Kumar, Bamshad Mobasher
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. These discovered clusters...