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The Eighth ACM SIGKDD International Conference on
Knowledge Discovery and Data Mining
July 23-26, 2002
Edmonton, Alberta, Canada
http://www.acm.org/sigkdd/kdd2002/
The 8th International Conference on Knowledge Discovery and Data Mining
welcomes participants during the four days between 23rd and 26th of July
2002. The Conference will take place in Edmonton few days apart from other
conferences such as AAAI, ISMB and other events
(see http://www.cs.ualberta.ca/Edmonton2002/).
This year the SIGKDD conference will have three parallel tracks: two tracks
of research papers in addition to the industrial track, a total of 44 papers
and 44 posters.
In addition, 6 workshops will be organized on July 23:
-2nd BIOKDD: Workshop on Data Mining in Bioinformatics
-4th WEBKDD: Web Mining for Usage Patterns and User Profiles
-3rd MDM/KDD: Workshop on Multimedia Data Mining
-MRDM Multi-Relational Data Mining
-2nd Workshop on Temporal Data Mining
-Fractals and Self-similarity in Data Mining: Issues and Approache
Six tutorials will be given during the conference:
-Multivariate Density Estimation and Visual Clustering
David W. Scott
-Text Mining for Bioinformatics
Hinrich Schuetze, Russ Altman
-Link Analysis : Current State of the Art
Ronen Feldman
-Common Reasons Data Mining Projects Fail
Monte F. Hancock
-Querying and Mining Data Streams: you only get one look
Rajeev Rastogi, Minos Garofalakis, Johannes Gehrke
-Visual Data Mining: Background, Techniques, and Drug Discovery Applications
Georges Grinstein, Mihael Ankerst, Daniel A. Keim
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The Early Registration Fee deadline is June 19, 2002
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For more details, please check the conference web site at:
http://www.acm.org/sigkdd/kdd2002/
The following are the accepted papers to be presented at the conference.
Full Research Papers:
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Query, Analysis, and Visualization of Hierarchically Structured Data using Polaris
Christopher Stolte, Diane Tang, Pat Hanrahan
DualMiner: A Dual-Pruning Algorithm for Itemsets with Constraints
Daniel Kifer, Cristian Bucila, Johannes Gehrke, Walker White
Pattern Discovery in Sequences under a Markov Assumption
Padhraic Smyth, Darya Chudova
Efficiently Mining Frequent Trees in a Forest
Mohammed Zaki
Relational Markov Models and their Application to Adaptive Web Navigation
Corin Anderson, Pedro Domingos, Daniel Weld
PEBL: Positive Example Based Learning for Web Page Classification Using SVM
Hwanjo Yu, Jiawei Han
Web Site Mining: A new way to spot Competitors, Customers and Suppliers in the World Wide Web
Matthias Schubert, Martin Ester, Hans-Peter Kriegel
On the Need for Time Series Data Mining Benchmarks: A Survey and Empirical Demonstration
Eamonn Keogh, Shruti Kasetty
Mining Frequent Item Sets by Opportunistic Projection
Junqiang Liu, Jiawei Han, Ke Wang, Yunhe Pan
ANF: A Fast and Scalable Tool for Data Mining in Massive Graphs
Christopher Palmer, Christos Faloutsos, Phillip Gibbons
Sequential Cost-Sensitive Decision Making with Reinforcement Learning
Edwin Pednault, Wei Fan, Haixun Wang, Naoki Abe, Bianca Zadrozny, Chidanand Apte
Mining Knowledge-Sharing Sites for Viral Marketing
Matthew Richardson, Pedro Domingos
On Interactive Visualization of high-dimensional Data using the Hyperbolic Plane
Jorg Walter
MARK: A Boosting Algorithm for Heterogeneous Kernel Models
Kristin Bennett, Michinari Momma, Mark Embrechts
Enhanced Word Clustering for Hierarchical Text Classification
Inderjit Dhillon, Subramanyam Mallela, Rahul Kumar
Bayesian analysis of massive datasets via particle filters
Greg Ridgeway, David Madigan
Optimizing Search Engines Using Clickthrough Data
Thorsten Joachims
Efficient Handling of High-Dimensional Feature Spaces by Randomized Classifier Ensembles
Kolcz Aleksander, xiaomei Sun, Jugal Kalita
Predicting Rare Classes: Can Boosting Make Any Weak Learner Strong?
Mahesh Joshi, Vipin Kumar, Ramesh Agarwal
Privacy Preserving Mining of Association Rules
Alexandre Evfimievski, Johannes Gehrke, Ramakrishnan Srikant, Rakesh Agrawal
Bursty and Hierarchical Structure in Streams
Jon Kleinberg
A Parallel Learning Algorithm for Text Classification
Canasai Kuengkrai, Chuleerat Jaruskulchai
Scalable Robust Covariance and Correlation Estimates for Data Mining
Fatemah ALqallaf, Ruben H. Zamar, Kjell Konis, Douglas Martin
Transforming Data to Satisfy Privacy Constraints
Vijay Iyengar
A Refinement Approach to Handling Model Misfit in Text Categorization
Tong Heng Phang, Bing Liu, Xiaoli Li Li, Haoran Wu
Shrinkage Estimator Generalizations of Proximal Support Vector Machines
Deepak Agarwal
Interactive Deduplication using Active Learning
Sunita Sarawagi,Anuradha Bhamidipaty
Hierarchical Model-Based Clustering of Large Datasets Through Fractionation and Refractionation.
Jeremy Tantrum, Werner Stuetzle, Alejandro Murua
On Effective Classification of Strings with Wavelets
Charu Aggarwal
Exploiting Unlabeled Data in Ensemble Methods
Kristin Bennett,Ayhan Demiriz, Richard Maclin
Querying Multiple Sets of Discovered Rules
Alexander Tuzhilin, Bing Liu
Selecting the Right Interestingness Measure for Association Patterns
Pang-Ning Tan, Vipin Kumar, Jaideep Srivastava
Full Industrial/Application Papers:
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Full Industrial/Application Papers:
Exploiting Response Models - Optimizing Cross-Sell and Up-Sell Opportunities in Banking
Andrew Storey, Marc-david Cohen
Learning Domain-Independent String Transformation Weights for High Accuracy Object Identification
Sheila Tejada, Craig A. Knoblock, Steven Minton
Mining Intrusion Detection Alarms for Actionable Knowledge
Klaus Julisch, Marc Dacier
Customer Lifetime Value Modeling and Its Use for Customer Retention Planning
Einat Neumann, Saharon Rosset, Uri Eick
A System for Real-time Competitive Market Intelligence
Sholom Weiss, Naval Verma
Learning Nonstationary Models of Normal Network Traffic for Detecting Novel Attacks
Matt Mahoney, Philip K. Chan
Handling Very Large Numbers of Association Rules in the Analysis of Microarray Data
Gediminas Adomavicius, Alexander Tuzhilin
Mining Product Reputations on the Web
Satoshi MORINAGA, Kenji Yamanishi, Kenji Tateishi, Toshikazu Fukushima
Interaction-pattern Mining for Software Requirements Recovery
Mohammad el-ramly, Eleni Stroulia, Paul Sorenson
On the potential of domain literature for Bayesian network learning and for clustering
Peter Antal, Patrick Glenisson, Geert Fannes, Janick Mathys, Bart De Moor, Yves Moreau
ADMIT: Anomaly-based Data Mining for Intrusions
Mohammed Zaki, karlton sequeira
Mining Heterogeneous Gene Expression with Time Lagged Recurrent Neural Networks
Yulan Liang, Arpad Kelemen
Poster Papers:
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Privacy Preserving Association Rule Mining in Vertically Partitioned Data
Jaideep Vaidya, Chris Clifton
Incremental Context Mining for Adaptive Document Classification
Rey-Long Liu, Yun-Ling Lu
Construct robust rule sets for classification
Jiuyong Li, Rodney Topor, Hong Shen
Tumor Cell Identification using Features Rules
Wynne Hsu, Mong Li Lee, Bin Fang
Combining Clustering and Co-training to Enhance Text Classification Using Unlabelled Data
Bhavani Raskutti, Adam Kowalczyk, Herman Ferra
Converting A Trained Neural Network To A Decision Tree DecText - Decision Tree Extractor
Olcay Boz
Finding all Surprising Patterns in a Time Series Database In Linear Time and Space
Eamonn Keogh, Bill 'Yuan-chi' Chiu, Stefano Lonardi
Topics in 0-1 data
Ella Bingham, Heikki Mannila, Jouni K. Seppanen
Scaling multi-class Support Vector Machines using inter-class confusion
Shantanu Godbole, Sunita Sarawagi, Soumen Chakrabarti
SyMP: An Efficient Clustering Approach to Identify Clusters of Arbitrary Shapes in Large Data Sets
Hichem Frigui
Distributed Data Mining in a Chain Store Database of Short Transactions
Cheng-Ru Lin, Chang-Hung Lee, Ming-Syan Chen, Philip Yu
CLOPE: A Fast and Effective Clustering Algorithm for Transactional Data
Yiling Yang, Xudong Guan, Jinyuan You
Instability of Decision Tree Classification Algorithms
Ruey-Hsia Li, Geneva Belford
SimRank: A Measure of Structural-Context Similarity
Glen Jeh, Jennifer Widom
Collusion in The U.S. Crop Insurance Program: Applied Data Mining
Bert Little, Walter Johnston, Ashley Lovell, Roderick Rejesus, Steve Steed
A Model for Discovering Customer Value for E-Content
Srinivasan Jagannathan, Jayanth Nayak, Kevin Almeroth, Markus Hofmann
Discovery Net: Towards a Grid of Knowledge Discovery
Patrick Wendel, Yike Guo, Vasa Curcin, Moustafa Ghanem, Martin Kohler, Jameel Syed,
Anthony Rowe
Mining Complex Models from Arbitrarily Large Databases in Constant Time
Geoff Hulten, Pedro Domingos
Integrating Feature and Instance Selection for Text Classification
Dimitris Meretakis, Dimitris Fragoudis, Spiros Likothanassis
A New Two-Phase Sampling Based Algorithm for Discovering Association Rules
Bin Chen, Haas Peter, Peter Scheuermann
A Theoretical Framework for Learning from a Pool of Disparate Data Sources
Shai Ben-David, Johannes Gehrke, Reba Schuller
Frequent Term-Based Text Clustering
Martin Ester, Xiaowei Xu, Florian Beil
CVS: A Correlation-Verification Based Smoothing Technique on Information Retrieval and Term
Clustering
Christina Yip Chung, Bin Chen
Topic-conditioned Novelty Detection
Jian Zhang,Yiming Yang, Jaime Carbonell, Chun Jin
A Robust and Efficient Clustering Algorithm based on Cohesion Self-Merging
Ming-Syan Chen, Cheng-Ru Lin
Sequential PAttern Mining Using Bitmaps
Jay Ayres, Johannes Gehrke, Tomi Yiu, Jason Flannick
Non-Linear Dimensionality Reduction Techniques for Classification and Visualization
Michail Vlachos, Dimitris Gunopulos, George Kollios, Carlotta Domeniconi, Niko Koudas
SECRET: A Scalable Linear Regression Tree Algorithm
Alin Dobra, Johannes Gehrke
Item Selection By "Hub-Authority" Profit Ranking
Ke Wang, Ming-Yen Thomas Su
Discovering Word Senses from Text
Dekang Lin, Patrick Pantel
Making every bit count: Fast nonlinear axis scaling
Leejay Wu, Christos Faloutsos
Clustering Seasonality Patterns in the Presence of Errors
Mahesh Kumar, Nitin Patel, Jonathan Woo
Learning to Match and Cluster Large High-Dimensional Data Sets For Data Integration
William Cohen, Jacob Richman
Transforming classifier scores into accurate multiclass probability estimates
Bianca Zadrozny, Charles Elkan
Single-shot Detection of Multiple Categories of Text using Parametric Mixture Models
Naonori Ueda, Kazumi Saito
B-EM: A Classifier Incorporating Bootstrap with EM Approach for Data Mining
Xintao Wu, Jianping Fan, Kalpathi Subramanian
Collaborative Crawling: Mining User Experiences for Topical Resource Discovery
Charu Aggarwal
A Unifying Framework for Outlier Detection and Change Point Detection from Non-stationary Time
Series Data
Kenji Yamanishi, Jun-ichi Takeuchi
Similarity Measure Based on Partial Information of Time series
Xiaoming Jin, Yuchang Lu, Chunyi Shi
Visualization Support for an User-Centered KDD Process
TrongDung Nguyen, Dung Nguyen Duc, Bao Ho Tu
What's the Code? Classification of Source Code Archives
Lee Giles, Secil Ugurel, Robert Krovetz, David Pennock, Eric Glover, Hongyuan Zha
Statistical Modeling of Large-Scale Simulation Data
Tina Eliassi-Rad, Terence Critchlow, Ghaleb Abdulla
Discovering Informative Content Blocks from Web Documents
Shian-Hua Lin, Jan-Ming Ho
Evaluating Classifiers Performance in a Constrained Environment
Anna Olecka
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Osmar R. ZAIANE, Ph.D. | office: ATH 352 (Athabasca Hall)
Assistant Professor (Prof. Adjoint) | e-mail: zaiane at cs.ualberta.ca
Department of Computing Science | phone : 1-780 492 2860
University of Alberta | fax : 1-780 492 1071
Edmonton, Alberta, T6G 2E8 Canada | http://www.cs.ualberta.ca/~zaiane/
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