Region Sampling: Continuous Adaptive Sampling on Sensor Networks (2009)
Song Lin, Benjamin Arai, Dimitrios Gunopulos, Gautam Das
Abstract — Satisfying energy constraints while meeting performance requirements is a primary concern when a sensor network is being deployed. Many recent proposed techniques offer error bounding...
Marios Hadjieleftheriou, George Kollios, Vassilis J. Tsotras, Dimitrios Gunopulos
The date of receipt and acceptance will be inserted by the editor Abstract Spatio-temporal objects — that is, objects that evolve over time — appear in many applications. Due to the nature of...
Vassilis Athitsos, Panagiotis Papapetrou, Michalis Potamias, George Kollios, Dimitrios Gunopulos
Time series data naturally appear in a wide variety of domains,including scientific measurements, financial data, sensor networks,
1 Introduction Fast Motion Capture Matching with Replicated Motion Editing (2008)
Marc Cardle, Michail Vlachos, Stephen Brooks, Dimitrios Gunopulos
Online Information Compression in Sensor Networks (2008)
Song Lin, Vana Kalogeraki, Dimitrios Gunopulos, Stefano Lonardi
Abstract-In the emerging area of wireless sensor networks, one of the most typical challenges is to retrieve historical information from the sensor nodes. Due to the resource limitation of sensor...
Information Retrieval in Peer-to-Peer Networks (2008)
D. Zeinalipour-yazti, Vana Kalogeraki, Dimitrios Gunopulos
Peer-to-Peer (P2P) systems are application layer networks which enable networked hosts to share resources in a distributed manner. An important problem in such networks is to be able to efficiently...
George Kollios, Dimitris Papadopoulos, Dimitrios Gunopulos, Vassilis J. Tsotras
Abstract. With the recent advances in wireless networks, embedded
Efficient Approximate Query Processing in Peer-to-Peer Networks (2008)
Benjamin Arai, Student Member, Gautam Das, Dimitrios Gunopulos, Vana Kalogeraki
Abstract—Peer-to-peer (P2P) databases are becoming prevalent on the Internet for distribution and sharing of documents, applications, and other digital media. The problem of answering large-scale...
Online Distribution Estimation for Streaming Data: Framework and Applications (2008)
Themis Palpanas, Vana Kalogeraki, Dimitrios Gunopulos
Abstract. In the last few years, we have been witnessing an evergrowing need for continuous observation and monitoring applications. This need is driven by recent technological advances that have...
Dimitrios Gunopulos, George Kollios, Vassilis J. Tsotras, Carlotta Domeniconi
Abstract. Estimating the selectivity of multidimensional range queries over real valued attributes has significant applications in data exploration and database query optimization. In this paper, we...
Song Lin, Vana Kalogeraki, Dimitrios Gunopulos, Walid A. Najjar
Flash memory is the most prevalent storage medium found on modern wireless sensor devices (WSDs). In this article we present two external memory index structures for the efficient retrieval of...
Dimitris Papadias, Yufei Tao, Jun Zhang, Nikos Mamoulis, Qiongmao Shen, Jimeng Sun, ...
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Time-Decaying Representations of Streaming Time Series (2008)
Themistoklis Palpanas, Michail Vlachos, Eamonn Keogh, Dimitrios Gunopulos
Abstract. During the last years we have witnessed a wealth of research on approximate representations for time series. The vast majority of the proposed approaches represent each value with...
pFusion: A P2P Architecture for Internet-Scale Content-Based Search and Retrieval (2008)
Demetrios Zeinalipour-yazti, Vana Kalogeraki, Dimitrios Gunopulos
Abstract—The emerging Peer-to-Peer (P2P) model has become a very powerful and attractive paradigm for developing Internet-scale systems for sharing resources, including files and documents. The...
Efficient Approximate Query Processing in Peer-to-Peer Networks (2008)
Benjamin Arai, Student Member, Gautam Das, Dimitrios Gunopulos, Vana Kalogeraki
Abstract—Peer-to-peer (P2P) databases are becoming prevalent on the Internet for distribution and sharing of documents, applications, and other digital media. The problem of answering large-scale...
ABSTRACT Answering Top-k Queries Using Views (2008)
Gautam Das, Dimitrios Gunopulos
The problem of obtaining efficient answers to top-k queries has attracted a lot of research attention. Several algorithms and numerous variants of the top-k retrieval problem have been introduced in...
Identifying Patterns- Trend analysis • A company's linear growth in sales over the years (2008)
Dimitrios Gunopulos (uc, Dimitrios Gunopulos, Gautam Das, Y Yl
A time series is a sequence of real numbers, representing the measurements of a real variable at equal time intervals- Stock price movements- Volume of sales over time- Daily temperature readings-...
An Efficient Density-based Approach for Data Mining Tasks (2008)
Carlotta Domeniconi, Dimitrios Gunopulos
Abstract. We propose a locally adaptive technique to address the problem of setting the bandwidth parameters for kernel density estimation. Our technique is efficient and can be performed in only two...
BUSINESS PROCESSES: BEHAVIOR PREDICTION AND CAPTURING REASONS FOR EVOLUTION (2008)
Sharmila Subramaniam, Vana Kalogeraki, Dimitrios Gunopulos
Abstract: Workflow systems are being used by business enterprises to improve the efficiency of their internal processes and enhance the services provided to their customers. Workflow models are the...
ABSTRACT Answering Top-k Queries Using Views (2008)
Gautam Das, Dimitrios Gunopulos, Dimitris Tsirogiannis
The problem of obtaining efficient answers to top-k queries has attracted a lot of research attention. Several algorithms and numerous variants of the top-k retrieval problem have been introduced in...
gmopuloQalmaden.ibm.com (2008)
Dimitrios Gunopulos, Heikki Mannila
Several data mining problems can be formulated as problems of finding maximally specific sentences that are interesting in a database. We first show that this problem has a close relationship with...
Song Lin, Vana Kalogeraki, Dimitrios Gunopulos, Walid A. Najjar
Flash Memory is the most prevalent storage medium found on modern Wireless Sensor Devices (WSDs). In this article we present two external memory index structures for the efficient retrieval of...
pFusion: A P2P Architecture for Internet-Scale Content-Based Search and Retrieval (2008)
Demetrios Zeinalipour-yazti, Vana Kalogeraki, Dimitrios Gunopulos
Abstract — The emerging Peer-to-Peer (P2P) model has become a very powerful and attractive paradigm for developing Internetscale systems for sharing resources, including files and documents. The...
Efficient Indexing Data Structures for Flash-Based Sensor Devices (2008)
Song Lin, Demetrios Zeinalipour-Yazti, Vana Kalogeraki, Dimitrios Gunopulos, Walid A. Najjar
this article we present two external memory index structures for the e#cient retrieval of records stored on the local flash memory of a WSD. Our index structures, MicroHash and MicroGF (Micro Grid...
Approximate embedding-based subsequence matching of time series (2008)
Vassilis Athitsos, Panagiotis Papapetrou, Michalis Potamias, George Kollios, Dimitrios Gunopulos
A method for approximate subsequence matching is introduced, that significantly improves the efficiency of subsequence matching in large time series data sets under the dynamic time warping (DTW)...
Approximating multi-dimensional aggregate (2007)
Dimitrios Gunopulos, George Kollios, Vassilis J. Tsotras, Carlotta Domeniconi
range queries over real attributes
Induction of Shallow Decision Trees (2007)
David Dobkin, Truxton Fulton, Dimitrios Gunopulos, Simon Kasif, Steven Salzberg
In this paper we describe efficient algorithms that induce shallow (i.e., low depth) decision trees. A key feature of these algorithms is their ability to induce decision trees over real-valued data...
Geometric Problems in Machine Learning. (2007)
David Dobkin, Dimitrios Gunopulos
We present some problems with geometric characterizations that arise naturally in practical applications of machine learning. Our motivation comes from a well known machine learning problem, the...
Ecient Local Flexible Nearest Neighbor Classi cation (2007)
Carlotta Domeniconi, Dimitrios Gunopulos
The nearest neighbor technique is a simple and appealing method to address classication problems. It relies on the assumption of locally constant class conditional probabilities. This assumption...
Information Retrieval in Peer-to-Peer Networks (2007)
D. Zeinalipour-yazti, Vana Kalogeraki, Dimitrios Gunopulos
Peer-to-Peer (P2P) systems are application layer networks which enable networked hosts to share resources in a distributed manner. An important problem in such networks is to be able to efficiently...
Ecient Biased Sampling for Approximate Clustering and Outlier Detection in Large Datasets (2007)
George Kollios, Dimitrios Gunopulos, Nick Koudas, Stefan Berchtold
We investigate the use of biased sampling according to the density of the dataset, to speed up the operation of general data mining tasks, such as clustering and outlier detection in large...
Adaptive Nearest Neighbor Classication using Support Vector Machines (2007)
Carlotta Domeniconi, Dimitrios Gunopulos
The nearest neighbor technique is a simple and appealing method to address classication problems. It relies on the assumption of locally constant class conditional probabilities. This assumption...
Data mining techniques for geospatial applications (2007)
Data mining is emerging as a new active area of research. The area combines methods and tools from the fields of databases, statistics and machine learning. Data mining techniques have been applied...
Submitted PODS 2001, paper ID: 118 Efficient Computation of (2007)
Donghui Zhang, Alexander Markowetz, Vassilis Tsotras, Dimitrios Gunopulos, Bernhard Seeger
A temporal aggregation query is an important but costly operation for applications that maintain timeevolving data (data warehouses, temporal databases, etc.). Due to the large volume of such data,...
Efficient Computation of Temporal Aggregates with Range Predicates (2007)
Extended Abstract, Donghui Zhang, Alexander Markowetz, Vassilis Tsotras, Dimitrios Gunopulos, Bernhard Seeger
A temporal aggregation query is an important but costly operation for applications that maintain time-evolving data (data warehouses, temporal databases, etc.). Due to the large volume of such data,...
Donghui Zhang, Er Markowetz, Vassilis Tsotras, Dimitrios Gunopulos, Bernhard Seeger, Author(s Donghui Zhang, ...
Individual participants
Multidimensional Membership Queries for Temporal Databases (2007)
Lifei Tan, Vassilis J. Tsotras, George Kollios, Dimitrios Gunopulos
Consider a dynamic set of multidimensional objects S, that evolves over time. A temporal membership query asks whether an object with given key attributes was in the set S at some time t. This paper...
Efficient Computation of Temporal Aggregates with Range Predicates (2007)
Extended Abstract, Donghui Zhang, Alexander Markowetz, Vassilis Tsotras, Dimitrios Gunopulos, Bernhard Seeger
A temporal aggregation query is an important but costly operation for applications that maintain time-evolving data (data warehouses, temporal databases, etc.). Due to the large volume of such data,...
Donghui Zhang, Vassilis J. Tsotras, Dimitrios Gunopulos, Bernhard Seeger
Temporal aggregation is an important but costly operation for applications that maintain time-evolving data (data warehouses, temporal databases, etc.). In this paper we examine the problem of...
George Kollios, Dimitrios Gunopulos, Vassilis J. Tsotras
Abstract. Nearest neighbor queries have received much interest in recent years due to their increased importance in advanced database applications. However, past work has addressed such queries in a...
Mining Process Models from Work ow Logs (2007)
Rakesh Agrawal, Dimitrios Gunopulos, Frank Leymann
Modern enterprises increasingly use the work ow paradigm to prescribe how business processes should be performed. Processes are typically modeled as annotated activity graphs. We present an approach...
Title Indexing Animated Objects Using Spatiotemporal Access Methods (2007)
George Kollios, Alex Delis, Dimitrios Gunopulos, Dimitrios Gunopulos, Vassilis Tsotras, ...
Individual participants
George Kollios, Dimitrios Gunopulos, Nick Koudas, Stefan Berchtold
We investigate the use of biased sampling according to the density of the dataset, to speed up the operation of general data mining tasks, such as clustering and outlier detection in large...
Submitted Pods' Paper, Donghui Zhang, Vassilis J. Tsotras, Dimitrios Gunopulos
We examine the problem of eciently computing sum/count/avg aggregates over objects with nonzero extent. Recent work on computing multi-dimensional aggregates has concentrated on objects with zero...
Temporal and Spatio-Temporal Aggregations over Data Streams using (2007)
Multiple Time Granularities, Donghui Zhang, Dimitrios Gunopulos, Vassilis J. Tsotras, Bernhard Seeger
this paper we examine the problem of computing such aggregates over data streams. The aggregates are maintained using multiple levels of temporal granularities: older data is aggregated using coarser...
Knowledge and Information Systems (2004) (2007)
Doi An Efficient, Carlotta Domeniconi, Dimitrios Gunopulos
We propose a locally adaptive technique to address the problem of setting the bandwidth parameters for kernel density estimation. Our technique is efficient and can be performed in only two dataset...
(alpha, k)-anonymity: an enhanced k-anonymity model for privacy preserving data publishing (2006)
Wong, Raymond Chi-Wing, Li, Jiuyong, Fu, Ada Wai-Chee, Wang, Ke, Eliassi-Rad, Tina, Ungar, Lyle H., ...
Privacy preservation is an important issue in the release of data for mining purposes. The k-anonymity model has been introduced for protecting individual identification. Recent studies show that a...
(alpha, k)-anonymity: an enhanced k-anonymity model for privacy preserving data publishing (2006)
Wong, Raymond Chi-Wing, Li, Jiuyong, Fu, Ada Wai-Chee, Wang, Ke, Eliassi-Rad, Tina, Ungar, Lyle H., ...
Privacy preservation is an important issue in the release of data for mining purposes. The k-anonymity model has been introduced for protecting individual identification. Recent studies show that a...
Locally adaptive metrics for clustering high dimensional data (2006)
Carlotta Domeniconi, Dimitrios Gunopulos, Sheng Ma, Dimitris Papadopoulos, Bojun Yan
Abstract. Clustering suffers from the curse of dimensionality, and similarity functions that use all input features with equal relevance may not be effective. We introduce an algorithm that discovers...
Combining Linguistic and Statistical Analysis to Extract Relations from Web Documents (2006)
Suchanek, Fabian M., Ifrim, Georgiana, Weikum, Gerhard, Eliassi-Rad, Tina, Ungar, Lyle, Craven, Mark, ...
abstract 1: The World Wide Web provides a nearly endless source of knowledge, which is mostly given in natural language. A first step towards exploiting this data automatically could be to extract...
A data compression technique for sensor networks with dynamic bandwidth allocation (2005)
Song Lin, Dimitrios Gunopulos, Vana Kalogeraki, Stefano Lonardi
Microhash: An efficient index structure for flash-based sensor devices (2005)
Demetrios Zeinalipour-yazti, Song Lin, Vana Kalogeraki, Dimitrios Gunopulos, Walid A. Najjar
In this paper we propose the MicroHash index, which is an efficient external memory structure for Wireless Sensor Devices (WSDs). The most prevalent storage medium for WSDs is flash memory. Our index...
Indexing mobile objects using dual transformations (2005)
Dimitris Papadopoulos, Dimitrios Gunopulos, Vassilis J. Tsotras
z UC Riverside
Selectivity estimators for multidimensional range queries over real attributes (2005)
Dimitrios Gunopulos, Vassilis J. Tsotras, Carlotta Domeniconi
Abstract Estimating the selectivity of multi-dimensional range queries over real valued attributes has significant applications in data exploration and database query optimization. In this paper we...
Adaptive Data Dissemination and Content-Driven Routing in Peer-to-Peer Systems (2005)
Dr. Vana Kalogeraki Chairperson, Dr. Dimitrios Gunopulos, Thomas S. Repantis, Thomas S. Repantis, Thomas S. Repantis
I would like to express my gratitude and appreciation to my advisor Dr. Vana Kalogeraki, for the inspiration and guidance, motivation and support she has offered me. I am also grateful to my...
Automatic Subspace Clustering of High Dimensional Data (2005)
Rakesh Agrawal, Johannes Gehrke, Dimitrios Gunopulos, Prabhakar Raghavan
Data mining applications place special requirements on clustering algorithms including: the ability to find clusters embedded in subspaces of high dimensional data, scalability, end-user...
Sensor network coverage restoration (2005)
Nitin Kumar, Dimitrios Gunopulos, Vana Kalogeraki
Abstract Wireless sensor networks are emerging as a new computational platform consisting of small, low-power and inexpensive nodes used in a broad set of application areas including environmental...
Exploiting Locality for Scalable Information Retrieval in Peer-to-Peer Networks (2005)
D. Zeinalipour-yazti, Vana Kalogeraki, Dimitrios Gunopulos
An important problem in unstructured peer-to-peer (P2P) networks is the efficient content-based retrieval of documents shared by other peers. However, existing searching mechanisms are not scaling...
Exploiting Locality for Scalable Information Retrieval in Peer-to-Peer Networks (2005)
D. Zeinalipour-yazti, Vana Kalogeraki, Dimitrios Gunopulos
An important problem in unstructured peer-to-peer (P2P) networks is the efficient content-based retrieval of documents shared by other peers. However, existing searching mechanisms are not scaling...
Indexing Mobile Objects Using Dual Transformations (2005)
George Kollios, Dimitris Papadopoulos, Dimitrios Gunopulos, Vassilis J. Tsotras
With the recent advances in wireless networks, embedded systems and GPS technology, databases that manage the location of moving objects have received increased interest. In this paper, we present...
MicroHash: An Efficient Index Structure for Flash-Based Sensor Devices (2005)
Demetrios Zeinalipour-yazti, Song Lin, Vana Kalogeraki, Dimitrios Gunopulos, Walid A. Najjar
In this paper we propose the MicroHash index, which is an efficient external memory structure for Wireless Sensor Devices (WSDs). The most prevalent storage medium for WSDs is flash memory. Our index...
Microhash: An efficient index structure for flash-based sensor devices (2005)
Demetrios Zeinalipour-yazti, Song Lin, Vana Kalogeraki, Dimitrios Gunopulos, Walid A. Najjar
In this paper we propose the MicroHash index, which is an efficient external memory structure for Wireless Sensor Devices (WSDs). The most prevalent storage medium for WSDs is flash memory. Our index...
Online amnesic approximation of streaming time series (2004)
Themistoklis Palpanas, Dimitrios Gunopulos
The past decade has seen a wealth of research on time series representations, because the manipulation, storage, and indexing of large volumes of raw time series data is impractical. The vast...
Iterative Incremental Clustering of Time Series (2004)
Jessica Lin Michail, Jessica Lin, Michail Vlachos, Eamonn Keogh, Dimitrios Gunopulos
We present a novel anytime version of partitional clustering algorithm, such as k-Means and EM, for time series. The algorithm works by leveraging off the multi-resolution property of wavelets. The...
Iterative Incremental Clustering of Time Series (2004)
Jessica Lin Michail, Jessica Lin, Michail Vlachos, Eamonn Keogh, Dimitrios Gunopulos
We present a novel anytime version of partitional clustering algorithm, such as k-Means and EM, for time series. The algorithm works by leveraging off the multi-resolution property of wavelets. The...
Online Amnesic Approximation of Streaming Time Series (2004)
Themistoklis Palpanas, Michail Vlachos, Eamonn Keogh, Dimitrios Gunopulos, Wagner Truppel
The past decade has seen a wealth of research on time series representations, because the manipulation, storage, and indexing of large volumes of raw time series data is impractical. The vast...
Indexing large human-motion databases (2004)
Eamonn Keogh, Themistoklis Palpanas, Victor B. Zordan, Dimitrios Gunopulos, Marc Cardle
Data-driven animation has become the industry standard for computer games and many animated movies and special effects. In particular, motion capture data recorded from live actors, is the most...
Clustering gene expression data in SQL using locally adaptive metrics (2003)
Dimitris Papadopoulos, Carlotta Domeniconi, Dimitrios Gunopulos, Sheng Ma
The clustering problem concerns the discovery of homogeneous groups of data according to a certain similarity measure. Clustering suers from the curse of dimensionality. It is not meaningful to look...
Distributed Deviation Detection in Sensor Networks (2003)
Themistoklis Palpanas, Dimitris Papadopoulos, Vana Kalogeraki, Dimitrios Gunopulos
Sensor networks have recently attracted much attention, because of their potential applications in a number of different settings. The sensors can be deployed in large numbers in wide geographical...
A Wavelet-Based Anytime Algorithm for K-Means Clustering of Time Series (2003)
Michail Vlachos, Jessica Lin, Eamonn Keogh, Dimitrios Gunopulos
The emergence of the field of data mining in the last decade has sparked an increasing interest in clustering of time series. Although there has been much research on clustering in general, most...
On-Line Discovery of Dense Areas in Spatio-Temporal Databases (2003)
Marios Hadjieleftheriou, George Kollios, Dimitrios Gunopulos, Vassilis J. Tsotras
Abstract — Moving object databases have received considerable attention recently. Previous work has concentrated mainly on modeling and indexing problems, as well as query selectivity estimation....
Efficient approximation of optimization queries under parametric aggregation constraints (2003)
Sudipto Guha, Dimitrios Gunopulos, Nick Koudas, Divesh Srivastava, Michail Vlachos
We introduce and study a new class of queries that we refer to as OPAC (optimization under parametric aggregation constraints) queries. Such queries aim to identify sets of database tuples that...
Indexing multi-dimensional time-series with support for multiple distance measures (2003)
Michail Vlachos, Marios Hadjieleftheriou, Dimitrios Gunopulos, Eamonn Keogh
Although most time-series data mining research has concentrated on providing solutions for a single distance function, in this work we motivate the need for a single index structure that can support...
Indexing multi-dimensional time-series with support for multiple distance measures (2003)
Michail Vlachos, Marios Hadjieleftheriou, Dimitrios Gunopulos, Eamonn Keogh
Although most time-series data mining research has concentrated on providing solutions for a single distance function, in this work we motivate the need for a single index structure that can support...
Discovering all most specific sentences (2003)
Dimitrios Gunopulos, Roni Khardon, Ram Sewak Sharma
Data mining can be viewed, in many instances, as the task of computing a representation of a theory of a model or a database, in particular by finding a set of maximally specific sentences satisfying...
Clustering Gene Expression Data in SQL Using Locally Adaptive Metrics (2003)
Dimitris Papadopoulos, Carlotta Domeniconi, Dimitrios Gunopulos, Sheng Ma
The clustering problem concerns the discovery of homogeneous groups of data according to a certain similarity measure. Clustering suffers from the curse of dimensionality. It is not meaningful to...
Temporal and Spatio-Temporal Aggregations over Data Streams using Multiple Time Granularities (2003)
Donghui Zhang, Dimitrios Gunopulos, Vassilis J. Tsotras, Bernhard Seeger
this paper we examine the problem of computing such aggregates over data streams. The aggregates are maintained using multiple levels of temporal granularities: older data is aggregated using coarser...
On-Line Discovery of Dense Areas in Spatio-temporal Databases (2003)
Marios Hadjieleftheriou, George Kollios, Dimitrios Gunopulos, Vassilis J. Tsotras
Moving object databases have received considerable attention recently. Previous work has concentrated mainly on modeling and indexing problems, as well as query selectivity estimation. Here we...
Discovering All Most Specific Sentences (2003)
Dimitrios Gunopulos, Roni Khardon, Heikki Mannila, Sanjeev Saluja, Hannu Toivonen, Ram Sewak Sharma
Data mining can be viewed, in many cases, as the task of computing a representation of a theory...
On-Line Discovery of Dense Areas in (2003)
Marios Hadjieleftheriou, George Kollios, Dimitrios Gunopulos, Vassilis J. Tsotras
Moving object databases have received considerable attention recently. Previous work has concentrated mainly on modeling and indexing problems, as well as query selectivity estimation. Here we...
Indexing Multi-Dimensional Time-Series with Support for (2003)
Multiple Distance Measures, Michail Vlachos, Marios Hadjieleftheriou, Dimitrios Gunopulos, Eamonn Keogh
Although most time-series data mining research has concentrated on providing solutions for a single distance function, in this work we motivate the need for a single index structure that can support...
Distributed Deviation Detection in Sensor Networks (2003)
Themistoklis Palpanas, Dimitris Papadopoulos, Vana Kalogeraki, Dimitrios Gunopulos
Sensor networks have recently attracted much attention, because of their potential applications in a number of different settings. The sensors can be deployed in large numbers in wide geographical...
Handling Multimedia Objects in Peer-to-Peer Networks (2002)
Vana Kalogeraki, Alex Delis, Dimitrios Gunopulos
Video-on-demand systems and services [4, 2] are predominantly offered over dedicated private networks with the help of large servers [3, 13]. Such systems are restricted by the number of concurrent...
D.: Efficient local flexible nearest neighbor classification (2002)
Carlotta Domeniconi, Dimitrios Gunopulos
The nearest neighbor technique is a simple and appealing method to address classification problems. It relies on the assumption of locally constant class conditional probabilities. This assumption...
Robust similarity measures for mobile object trajectories (2002)
Michail Vlachos, Dimitrios Gunopulos, George Kollios
We investigate techniques for similarity analysis of spatio-temporal trajectories for mobile objects. Such kind of data may contain a great amount of outliers, which degrades the performance of...
Handling Multimedia Objects in Peer-to-Peer Networks (2002)
Vana Kalogeraki, Alex Delis, Dimitrios Gunopulos
Video-on-demand systems and services [4, 2] are predominantly offered over dedicated private networks with the help of large servers [3, 13]. Such systems are restricted by the number of concurrent...
Non-Linear Dimensionality Reduction Techniques for Classification and Visualization (2002)
Michail Vlachos, Carlotta Domeniconi, Dimitrios Gunopulos, George Kollios, Nick Koudas
In this paper we address the issue of using local embeddings for data visualization in two and three dimensions, and for classi cation. We advocate their use on the basis that they provide an ecient...
Temporal aggregation over data streams using multiple granularities (2002)
Donghui Zhang, Dimitrios Gunopulos, Vassilis J. Tsotras, Bernhard Seeger
Temporal aggregation is an important but costly operation for applications that maintain time-evolving data (data warehouses, temporal databases, etc.). In this paper we examine the problem of...
Efficient aggregation over objects with extent (2002)
Donghui Zhang, Vassilis J. Tsotras, Dimitrios Gunopulos
We examine the problem of eciently computing sum/count/ avg aggregates over objects with non-zero extent. Recent work on computing multi-dimensional aggregates has concentrated on objects with zero...
J. Tsotras, Dr. Chinya Ravishankar, Dr. Dimitrios Gunopulos, Donghui Zhang, Donghui Zhang
I would like to express my sincere gratitude to my thesis advisor, Professor Vassilis J. Tsotras for his excellent guidance throughout the course of this dissertation and for his support during my...
Adaptive nearest neighbor classification using support vector machines (2002)
Carlotta Domeniconi, Dimitrios Gunopulos
The nearest neighbor technique is a simple and appealing method to address classification problems. It relies on the assumption of locally constant class conditional probabilities. This assumption...
Efficient aggregation over objects with extent (2002)
Donghui Zhang, Vassilis J. Tsotras, Dimitrios Gunopulos, Alexander Markowetz
We examine the box-sum aggregation problem, i.e., how to efficiently compute sum/count/avg aggregates over objects with extent. Such aggregation arise often in spatial and spatiotemporal...
Adaptive nearest neighbor classification using support vector machines (2002)
Carlotta Domeniconi, Dimitrios Gunopulos
The nearest neighbor technique is a simple and appealing method to address classification problems. It relies on the assumption of locally constant class conditional probabilities. This assumption...
Efficient indexing of spatiotemporal objects (2002)
Marios Hadjieleftheriou, George Kollios, Vassilis J. Tsotras, Dimitrios Gunopulos
Spatiotemporal objects, i.e., objects which change their position and/or extent over time appear in many applications. In this paper we examine the problem of indexing large volumes of such data....
Temporal aggregation over data streams using multiple granularities (2002)
Donghui Zhang, Dimitrios Gunopulos, Vassilis J. Tsotras, Bernhard Seeger
Abstract. Temporal aggregation is an important but costly operation for applications that maintain time-evolving data (data warehouses, temporal databases, etc.). In this paper we examine the problem...
Discovering similar multidimensional trajectories (2002)
Michail Vlachos, George Kollios, Dimitrios Gunopulos
We investigate techniques for analysis and retrieval of object trajectories in a two or three dimensional space. Such kind of data usually contain a great amount of noise, that makes all previously...
Efficient Biased Sampling for Approximate Clustering and Outlier Detection in Large Datasets (2002)
George Kollios, Ieee Computer Society, Dimitrios Gunopulos, Nick Koudas, Stefan Berchtold
Abstract---We investigate the use of biased sampling according to the density of the data set to speed up the operation of general data mining tasks, such as clustering and outlier detection in large...
Locally adaptive metric nearest-neighbor classification (2002)
Carlotta Domeniconi, Jing Peng, Dimitrios Gunopulos
Nearest neighbor classification assumes locally constant class conditional probabilities. This assumption becomes invalid in high dimensions with finite samples due to the curse of dimensionality....
Locally adaptive metric nearest-neighbor classification (2002)
Carlotta Domeniconi, Jing Peng, Dimitrios Gunopulos
Nearest neighbor classification assumes locally constant class conditional probabilities. This assumption becomes invalid in high dimensions with finite samples due to the curse of dimensionality....
Chotirat Ann Ratanamahatana, Dimitrios Gunopulos
ItisknownthatNaveBayesianclassifier(NB)worksverywellonsome domains,andpoorlyonsome.TheperformanceofNBsuffersindomainsthat involvecorrelatedfeatures.C4.5decisiontrees,ontheotherhand,typically...
Temporal Aggregation over Data Streams using Multiple Granularities (2002)
Donghui Zhang, Dimitrios Gunopulos, Vassilis J. Tsotras, Bernhard Seeger
Temporal aggregation is an important but costly operation for applications that maintain time-evolving data (data warehouses, temporal databases, etc.). In this paper we examine the problem of...
Efficient indexing of spatiotemporal objects (2002)
Marios Hadjieleftheriou, George Kollios, Dimitrios Gunopulos, Vassilis J. Tsotras
Abstract — Spatiotemporal objects i.e., objects which change their position and/or extent over time, appear in many applications. This paper addresses the problem of indexing large volumes of such...
Efficient and tunable similar set retrieval (2001)
Aristides Gionis, Dimitrios Gunopulos, Nick Koudas
Set value attributes are a concise and natural way to model complex data sets. Modern Object Relational systems support set value attributes and allow various query capabilities on them. In this...
Indexing Animated Objects Using Spatiotemporal Access Methods (2001)
George Kollios, Vassilis J. Tsotras, Dimitrios Gunopulos, Alex Delis, Marios Hadjieleftheriou
AbstractÐWe present a new approach for indexing animated objects and efficiently answering queries about their position in time and space. In particular, we consider an animated movie as a...
Incremental support vector machine construction (2001)
Carlotta Domeniconi, Dimitrios Gunopulos
SVMs suffer from the problem of large memory requirement and CPU time when trained in batch mode on large data sets. We overcome these limitations, and at the same time make SVMs suitable for...
Incremental support vector machine construction (2001)
Carlotta Domeniconi, Dimitrios Gunopulos
SVMs suffer from the problem of large memory requirement and CPU time when trained in batch mode on large data sets. The training process, in fact, involves the solution of a quadratic programming...
Carlotta Domeniconi, Dimitrios Gunopulos
We propose a locally adaptive technique to address the problem of setting the bandwidth parameters optimally for kernel density estimation. Our technique is efficient and can be performed in only two...
Indexing Animated Objects Using Spatiotemporal Access Methods (2001)
George Kollios, Dimitrios Gunopulos, Vassilis J. Tsotras, Alex Delis, Marios Hadjieleftheriou
We present a new approach for indexing animated objects and eciently answering queries about their position in time and space. In particular, we consider an animated movie as a spatiotemporal...
An adaptive metric machine for pattern classification (2001)
Carlotta Domeniconi, Jing Peng, Dimitrios Gunopulos
Nearest neighbor classification assumes locally constant class conditional probabilities. This assumption becomes invalid in high dimensions with finite samples due to the curse of dimensionality....
ÌIME�ENTER È�ÖØ � �Ô�ÒØ× (2001)
George Kollios, Dimitrios Gunopulos, Vassilis Tsotras, Alex Delis, Ùø�óö George Kollios, Dimitrios Gunopulos, ...
Any software made available via TIMECENTER is provided “as is ” and without any express or implied warranties, including, without limitation, the implied warranty of merchantability and fitness...
Efficient Computation of Temporal Aggregates with Range Predicates (2001)
Donghui Zhang, Dimitrios Gunopulos
A temporal aggregation query is an important but costly operation for applications that maintain time-evolving data (data warehouses, temporal databases, etc.). Due to the large volume of such data,...
Indexing Animated Objects Using Spatiotemporal Access Methods (2000)
George Kollios, Dimitrios Gunopulos, Vassilis Tsotras, Alex Delis, Marios Hadjieleftheriou
We present a new approach for indexing animated objects and efficiently answer queries over their position in time and space. In particular, we consider an animated movie as a spatiotemporal...
Approximating Multi-Dimensional Aggregate Range Queries Over Real Attributes (2000)
Dimitrios Gunopulos, George Kollios, Vassilis J. Tsotras, Carlotta Domeniconi
Finding approximate answers to multi-dimensional range queries over real valued attributes has significant applications in data exploration and database query optimization. In this paper we consider...
Approximating Multi-Dimensional Aggregate Range Queries Over Real Attributes (2000)
Dimitrios Gunopulos, George Kollios, Vassilis J. Tsotras, Carlotta Domeniconi
Finding approximate answers to multi-dimensional range queries over real valued attributes has significant applications in data exploration and database query optimization. In this paper we consider...
Title E cient Computation of Temporal Aggregates with Range Predicates (2000)
Donghui Zhang, Er Markowetz, Vassilis Tsotras, Dimitrios Gunopulos, Bernhard Seeger, Dimitrios Gunopulos, ...
Any software made available via TimeCenter is provided \as is " and without any express or implied warranties, including, without limitation, the implied warranty of merchantability and...
Dimitrios Gunopulos Pi, Dimitrios Gunopulos
Title: Data Mining Techniques for Geospatial Applications
Indexing Animated Objects (1999)
George Kollios, Dimitrios Gunopulos, Vassilis J. Tsotras
We examine the problem of indexing objects in animated movies. We consider an animated movie as consisting of a frame sequence where each frame is described by objects in a 2-dimensional space. The...
Indexing Animated Objects (1999)
George Kollios, Dimitrios Gunopulos, Vassilis J. Tsotras
We examine the problem of indexing objects in animated movies. We consider an animated movie as consisting of a frame sequence where each frame is described by objects in a 2-dimensional space. The...
On Indexing Mobile Objects (1999)
George Kollios, Dimitrios Gunopulos, Vassilis J. Tsotras
We show how to index mobile objects in one and two dimensions using efficient dynamic external memory data structures. The problem is motivated by real life applications in traffic monitoring,...
Constraint-Based Rule Mining in Large, Dense Databases (1999)
Roberto J. Bayardo, Roberto J. Bayardo, Rakesh Agrawal, Rakesh Agrawal, Dimitrios Gunopulos, ...
: Constraint-based rule miners find all rules in a given data-set meeting user-specified constraints such as minimum support and confidence. We describe a new algorithm that exploits all...
On Indexing Mobile Objects (1999)
George Kollios, Dimitrios Gunopulos, Vassilis J. Tsotras
We show how to index mobile objects in one and two dimensions using efficient dynamic external memory data structures. The problem is motivated by real life applications in traffic monitoring,...
Mining Process Models from Workflow Logs (1998)
Agrawal, Rakesh, Gunopulos, Dimitrios, Leymann, Frank
Modern enterprises increasingly use the workflow paradigm to prescribe how business processes should be performed. Processes are typically modeled as annotated activity graphs. We present an approach...
Automatic subspace clustering of high dimensional data for data mining applications (1998)
Rakesh Agrawal, Johannes Gehrke, Dimitrios Gunopulos, Prabhakar Raghavan
Data mining applications place special requirements on clustering algorithms including: the ability to nd clusters embedded in subspaces of high dimensional data, scalability, end-user...
Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications (1998)
Rakesh Agrawal, Johannes Gehrke, Dimitrios Gunopulos, Prabhakar Raghavan
Data mining applications place special requirements on clustering algorithms including: the ability to find clusters embedded in subspaces of high dimensional data, scalability, end-user...
Time-Series Similarity Problems and Well-Separated Geometric Sets (1998)
Béla Bollobas, Gautam Das, Dimitrios Gunopulos, Heikki Mannila
Given a pair of nonidentical complex objects, defining (and determining) how similar they are to each other is a nontrivial problem. In data mining applications, one frequently needs to determine the...
Mining Process Models from Workflow Logs (1998)
Rakesh Agrawal, Dimitrios Gunopulos, Frank Leymann
Modern enterprises increasingly use the workflow paradigm to prescribe how business processes should be performed. Processes are typically modeled as annotated activity graphs. We present an approach...
Mining Process Models from Workflow Logs (1998)
Rakesh Agrawal, Dimitrios Gunopulos, Frank Leymann
Modern enterprises increasingly use the workflow paradigm to prescribe how business processes should be performed. Processes are typically modeled as annotated activity graphs. We present an approach...
Automatic subspace clustering of high dimensional data for data mining applications (1998)
Rakesh Agrawal, Johannes Gehrke, Dimitrios Gunopulos, Prabhakar Raghavan
Data mining applications place special requirements on clustering algorithms including: the ability to nd clusters embedded in subspaces of high dimensional data, scalability, end-user...
Time-Series Similarity Problems and Well-Separated Geometric Sets (1997)
Ela Bollob'as, Gautam Das, Dimitrios Gunopulos, Heikki Mannila
Given a pair of nonidentical complex objects, defining (and determining) how similar they are to each other is a nontrivial problem. In data mining applications, one frequently needs to determine the...
Data mining, hypergraph transversals, and machine learning (1997)
Dimitrios Gunopulos, Roni Khardon, Heikki Mannila, Hannu Toivonen
Several data mining problems can be formulated as problems of finding maximally specific sentences that are interesting in a database. We first show that this problem has a close relationship with...
Data mining, Machine Learning (1997)
Dimitrios Gunopulos, Roni Khardon, Heikki Mannila, Hannu Toivonen
Several data mining problems can be formulated as problems of finding maximally specific sentences that are interesting in a database. We first show that this problem has a close relationship with...
Data mining, Hypergraph Transversals, and Machine Learning (1997)
Dimitrios Gunopulos, Roni Khardon, Heikki Mannila, Hannu Toivonen
Several data mining problems can be formulated as problems of finding maximally specific sentences that are interesting in a database. We first show that this problem has a close relationship with...
Mining Process Models from Work ow Logs (1997)
Rakesh Agrawal, Dimitrios Gunopulos, Frank Leymann
Abstract. Modern enterprises increasingly use the work ow paradigm to prescribe how business processes should be performed. Processes are typically modeled as annotated activity graphs. We present an...
Concept Learning with geometric hypotheses (1995)
David P. Dobkin, Dimitrios Gunopulos, David P
We present a general approach to solving the minimizing disagreement problem for geometric hypotheses with finite VC-dimension. These results also imply efficient agnostic-PAC learning of these...