ICDM '01
The 2001 IEEE International Conference on Data Mining

ICDM 2001 Program

Notes for poster paper authors:

Each poster review on November 30 in the afternoon has a 10 min presentation.
At the Posters and Software Demos session (November 30 6:30pm - 9:00pm), each poster paper can have around 12 sheets (A4 or similar size) for posting. The conference will provide a set of white foam paper for each poster paper.

November 29
	Tutorials (Montery Room)	Workshop (Carmel Room)	Workshop (Santa Clara Room)
9:00	Text Mining for Bioinformatics by Hinrich Schuetze	Integrating Data Mining and Knowledge Management	Text Mining (TextDM '2001)
2:00	Mining Time Series Data by Eamonn Keogh	Integrating Data Mining and Knowledge Management	Text Mining (TextDM '2001)
November 30
8:30	Opening/Awards (Cascade Sierra Room)
9:00	Keynote: Jim Gray, Microsoft Research, USA (The 1999 Turing Award Winner). The World Wide Telescope: Mining the Sky Cascade Sierra Room
10:00	Catered Break (Bayshore Foyer)
10:30	Cascade Room Research Track 1A:	Sierra Room Research Track 2A:	Siskiyou Room Research Track 3A
1	S115 G Richards, V J Rayward-Smith Discovery of Association Rules in Tabular Data	S321 Jose Balcazar, Yang Dai, Osamu Watanabe Provably Fast Training Algorithms for Support Vector Machines	S305 Steven Noel, Vijay Raghavan, C.-H. Henry Chu Visualizing Association Mining Results through Hierarchical Clusters
2	S451 Masakazu Seno, George Karypis LPMiner: An Algorithm for Finding Frequent Itemsets Using Length-Decreasing Support Constraint	S424 David Maxwell Chickering, Christopher Meek, Robert Rounthwaite Efficient Determination of Dynamic Split Points in a Decision Tree	S541 Beitao Li, Wei-Cheng Lai, Edward Chang, Kwang-Ting Cheng Mining Image Features for Efficient Query Processing
3	S426 Floris Geerts, Bart Goethals, Jan Van den Bussche A Tight Upper Bound on the Number of Candidate Patterns	S475 Tom Fawcett Using Rule Sets to Maximize ROC Performance	S348 Jong-Sheng Cherng, Mei-Jung Lo A Hypergraph Based Clustering Algorithm for Spatial Data Sets
12:00	Lunch (ICDM Steering Committee Meeting with ICDM '02 Organizers)
1:30	Cascade Room Research Track 1B:	Sierra Room Research Track 2B:	Siskiyou Room Research Track 3B
4	S458 Chang-Shing Perng, Haixun Wang, Sheng Ma, Joself L. Hellerstein FARM: A Framework for Exploring Mining Spaces with Multiple Attributes	S402 Maria Halkidi, Michalis Vazirgiannis Clustering Validity Assessment: Finding the Optimal Partitioning of Set	S377 Ming-Chuan Hung, Don-Lin Yang An Efficient Fuzzy C-Means Clustering Algorithm
5	S488 Karam Gouda, Mohammed J. Zaki Efficiently Mining Maximal Frequent Itemsets	S304 Manoranjan Dash, Kian Lee Tan, Huan Liu Efficient Yet Accurate Clustering	S349 Richard J Bolton, David J Hand Significance Tests for Patterns in Continuous Data
6	S551 J. Li, H. Shen, and R. Topor Mining the Smallest Association Rule Set for Predictions	S273 Valerie Guralnik, George Karypis A Scalable Algorithm for Clustering Sequential Data	S457 Wei Wang, Jiong Yang, Philip Yu Meta-Patterns: Revealing Hidden Periodic Patterns
7	S179 Bing Liu, Yiming Ma, and R. Lee Analyzing the Interestingness of Association Rules from the Temporal Dimension	S404 Konstantinos Kalpakis, Dhiral Gada, Vasundhara Puttagunta Distance Measures for Effective Clustering of ARIMA Time-Series	S306 Wai-Ho Au, Keith C.C. Chan Classification with Degree of Membership: A Fuzzy Approach
8	S522 Chang-Hung Lee, Cheng-Ru Lin, Ming-Syan Chen On Mining General Temporal Assocation Rules in a Publication Database	S398 Hichem Frigui, Mohamed Ben Hadj Rhouma A Synchronization Based Algorithm for Discovering Ellipsoidal Clusters in Large Datasets	S176 Tzung-Pei Hong, Yeong-Chyi Lee Mining Coverage-Based Fuzzy Rules by Evolutional Computation
4:00	Catered Break (Bayshore Foyer)
4:30	Cascade Room Research Track 1C Poster Previews (See below)	Sierra Room Research Track 2C Poster Previews (See below)	Siskiyou Room Research Track 3C Poster Previews (See below)
5:45	Break
6:30 - 9:00	Posters and Software Demos (Donner Room)
December 1
8:30	Keynote: Jerome H. Friedman, Stanford University, USA. Predictive Data Mining with Multiple Additive Regression Trees Cascade Sierra Room
9:30	Catered Break (Bayshore Foyer)
10:00	Cascade Room Research Track 1D:	Sierra Room Research Track 2D:	Siskiyou Room Research Track 3D:
9	S442 Marzena Kryszkiewicz Concise Representation of Frequent Patterns Based on Disjunction-Free Generators	S418 Haixun Wang, Philip S. Yu SSDT: A Scalable Subspace-Splitting Classifier for Biased Data	S491 Hisao Ishibuchi, Takashi Yamamoto, Tomoharu Nakashima Fuzzy Data Mining: Effect of Fuzzy Discretization
10	S408 Christopher Jermaine The Computational Complexity of High-Dimensional Correlation Search	S568 Shoji Hirano, Shusaku Tsumoto Indiscernability Degress of Objects for Evaluating Simplicity of Knowledge in the Clustering Procedure	S527 Paul Munteanu, Mohamed Bendou The EQ Framework for Learning Equivalence Classes of Bayesian Networks
11	S512 Wenmin Li, Jiawei Han, Jian Pei CMAR: Accurate and Efficient Classification Based on Multiple Class-Association Rules	S311 SungYoung Jung, Taek-Soo Kim An Agglomerative Hierarchical Clustering Using partial Maximum Array and Incremental Similarity Computation Method	S396 Lior Rokach, Oded Maimon Theory and Applications of Attribute Decomposition
12	S423 Sheng Ma, Joseph L. Hellerstein Mining Mutually Dependent Patterns	S409 Tapio Elomaa, Juho Rousu Preprocessing Opportunities in Optimal Numerical Range Partitioning	S519 Rong Chen, Krishnamoorthy Sivakumar, Hillol Kargupta Distributed Web Mining Using Bayesian Networks from Multiple Data Streams
12:00	Lunch
1:30	Keynote: Pat Langley, Institute for the Study of Learning and Expertise, USA. Knowledge and Data in Computational Scientific Discovery Cascade Sierra Room
2:30	Catered Break (Bayshore Foyer)
3:00	Cascade Room Research Track 1 E:	Sierra Room Research Track 2 E:	Siskiyou Room Research Track 3 E:
13	S310 Sigal Sahar Interestingness PreProcessing	S486 Mahesh V. Joshi, Vipin Kumar, Ramesh Agarwal Evaluating Boosting Algorithms to Classify Rare Classes: Comparison and Improvements	S469 Joaquim Silva, Agra Coelho, Gabriel Lopes Document Clustering and Cluster Topic Extraction in Multilingual Corpora
14	S160 Xiaohua Tony Hu Using Rough Sets Theory and Database Operations to Construct a Good Ensemble of Classifiers for Data Mining Applications	S430 Wei Fan, Matthew Miller, Salvatore J. Stolfo, Wenke Lee, and P. Chan Using Artificial Anomalies to Detect Unknown and Known Network Intrusions	S238 Henry E. Kyburg, Jr. Statistical Considerations in Learning from Data
15	S283 Ying Sai, Yiyu Yao, Ning Zhong Data Analysis and Mining in Ordered Information Tables	S242 Ning Zhong, Y.Y. Yao, Muneaki Ohshima, Setsuo Ohsuga Interestingness, Peculiarity, and Multi-database Mining	S393 Johan Himberg, Kalle Korpiaho, Heikki Mannila, Johanna Tikanmäki, and Toivonen Time Series Segmentation for Context Recognition in Mobile Devices
16	S372 Thomas Knight, Jon Timmis AINE: An Immunological Approach to Data Mining	S570 Suhail Ansari, Ron Kohavi, Llew Mason, Zijian Zheng Integrating E-Commerce and Data Mining: Architecture and Challenges	S132 Charu Aggarwal, Philip Yu On Effective Conceptual Indexing and Similarity Search in Text Data
5:00	Break
6:30 – 8:30	Banquette (Cascade Sierra Room)
December 2
8:30	Keynote:Benjamin W. Wah, University of Illinois, Urbana-Champaign, USA (President, IEEE Computer Society). Intelligent Mining for Time Series Predictions Cascade Sierra Room
9:30	Catered Break (Bayshore Foyer)
10:00	Cascade Room Research Track 1G:	Sierra Room Research Track 2G:	Siskiyou Room Research Track 3G:
17	S515 C. Ordonez, E. Omiecinski, L. de Braal, C. Santana, N. Ezquerra, J. Taboada, D. Cooke, E. Krawczynska, and E. Garcia Mining Constrained Association Rules to Predict Heart Disease	S516 Gary R. Livingston, John M. Rosenberg, Bruce G. Buchanan Closing the Loop: An Agenda- and Justification-Based Framework for Selecting the Next Discovery Task to Perform	S362 Henner Graubitz, Myra Spiliopoulou, Karsten Winkler The DIAsDEM Framework for Converting Domain-Specific Texts into XML Documents with Data Mining Techniques
18	S422 Jian Pei, Jiawei Han, Hongjun Lu, Shojiro Nishio, S. Tang, and D. Yang H-Mine: Hyper-Structure Mining of Frequent Patterns in Large Databases	S545 Gary Livingston, John M. Rosenberg, Bruce G. Buchanan Closing the Loop: Heuristics for Autonomous Discovery	S250 Wen-Hsiang Lu, Lee-Feng Chien, Hsi-Jian Lee Anchor Text Mining for Translation of Web Queries
19	S386 Kimmo Raivio, Olli Simula, Jaana Laiho Neural Analysis of Mobile Radio Access Network	S504 Ching-Yao Wang, Tzung-Pei Hong, Shian-Shyong Tseng Maintenance of Sequential Patterns for Record Deletion	S530 Catherine Blake, Wanda Pratt Better Rules, Few Features: A Semantic Approach to Selecting Features from Text
20	S390 Hillol Kargupta, Byung-Hoon Park Mining Decision Trees from Data Streams in a Mobile Environment	S370 Pierre-Yves ROLLAND FlExPat: Flexible Extraction of Sequential Patterns	S463 Zarrin Langari, Frank Wm. Tompa Subject Classification in the Oxford English Dictionary
12:00	Lunch
1:30	Cascade Room Research Track 1H:	Sierra Room Research Track 2H:	Siskiyou Room Research Track 3H:
21	S253 AIXIN SUN, EE-PENG LIM Hierarchical Text Classification and Evaluation	S161 Eamonn Keogh, Selina Chu, David Hart, Michael Pazzani An Online Algorithm for Segmenting Time Series	S272 Xiaofeng He, Chris Ding, Hongyuan Zha, Horst Simon Automatic Topic Identification Using Webpage Clustering
22	S410 Joao Gama Functional Trees for Classification	S144 Michael Anderson Knowledge Discovery from Diagrammatically Represented Data	S164 Krishna Bharat, Bay-Wei Chang, Monika Henzinger, Matthias Ruhl Who Links to Whom: Mining Linkage between Web Sites
23	S561 Aijun An, Yuanyuan Wang Comparisons of Classification Methods for Screening Potential Compounds	S531 Chris Ding, Xiaofeng He, Hongyuan Zha, Ming Gu, and H.Simon A Min-Max Cut Algorithm for Graph Partitioning and Data Clustering	S322 Jung-Won Lee, Kiho Lee, Won Kim Preparations for Semantics-Based XML Mining
24	S316 Virginia Wheway Using Boosting to Simplify Classification Models	S498 Michihiro Kuramochi, George Karypis Frequent Subgraph Discovery
3:30	Catered Break (Bayshore Foyer)
4:00	Panel: Data Mining: How Research Meets Practical Development? Cascade Sierra Room Chair: Rao Kotagiri, University of Melbourne, Australia. Panel Members: Pat Langley, Institute for the Study of Learning and Expertise, USA. Gregory Piatetsky-Shapiro, KDnuggets, USA. Philip Yu, IBM T.J. Watson Research Center, USA. Benjamin W. Wah, University of Illinois, Urbana-Champaign, USA.
5:00	Adjourn

Cascade Room
Research Track 1C

S474 Osmar R. Zaiane, Mohammad El-Hajj, Paul Lu Fast Parallel Association Rule Mining without Candidacy Generation

S467 Wolfgang Gaul, Lars Schmidt-Thieme Mining Generalized Association Rules for Sequential and Path Data

S567 Honghua Dai Inexact Field Learning: An Approach to Induce High Quality Rules from Low Quality Data

S445 Viviane Crestana Jensen, Nandit Soparkar Heuristic Optimization for Decentralized Frequent Itemset Counting

S371 Viet Phan-Luong The Representative Basis for Association Rules

S162 Fan-Chen Tseng, Ching-Chi Hsu, H. Chen Mining Frequent Closed Itemsets with the Frequent Pattern List

S308 Hasan M. Jamil Ad Hoc Association Rule Mining as SQL3 Queries

S257 Show-Jane Yen, Yue-Shi Lee
An Efficient Data Mining Technique for Discovering Interesting Sequential Patterns

S485 Carlotta Domeniconi, Dimitrios Gunopulos Incremental Support Vector Machine Construction

S464 Sherri K. Harms, Jitender Deogun, Jamil Saquer, Tsegaye Tadesse Discovering Representative Episodal Association Rules from Event Sequences Using Frequent Closed Episode Sets and Event Constraints

Sierra Room
Research Track 2C

S361 Jie Chen, Haiying Li, Shiwei Tang Association Rules Enhanced Classification of Underwater Acoustic Signal

S401 Samuel Steingold, Richard Wherry, Gregory Piatetsky-Shapiro Measuring Real-Time Predictive Models

S278 Pascal Soucy, Guy W. Mineau A Simple KNN Algorithm for Text Categorization

S513 Carlos Ordonez, Edward Omiecinski, N. Ezquerra A Fast Algorithm to Cluster High Dimensional Basket Data

S130 D. Zhang, Q. Ha, M. Lu Mining California Vital Statistics Data

S336 Fernando Alonso, ,Juan P. Caraça-Valente, Loïc Martínez, Cesar Montes
Discovering Similar Patterns for Characterizing Time Series in a Medical Domain

S332 Tadashi Nomoto, Yuji Matsumoto An Experimental Comparison of Supervised and Unsupervised Approaches to Text Summarization

S338 Daniel Gillblad, Anders Holst Dependency Derivation in Industrial Process Data

S240 Xiong Wang a-Surface and Its Application to Mining Protein Data

S260 Petri Myllymaki, Tomi Silander, Henry Tirri, Pekka Uronen Bayesian Data Mining on the Web with B-Course

S347 Bernard Zenko, Ljupco Todorovski, Saso Dzeroski A Comparison of Stacking with Meta Decision Trees to Bagging, Boosting, and Stacking with other Methods

Siskiyou Room
Research Track 3C

S505 X. Liang, and Y. Liang Applications of Data Mining in Hydrology

S202 Tobias Scheffer, Christian Decomain, Stefan Wrobel Mining the Web with Active Hidden Markov Models

S181 Gang LI, Fu Tong, Honghua Dai
Evolutionary Structure Learning Algorithm for Bayesian Network and Penalized Mutual Information Metric

S206 June-Suh Cho, Nabil R. Adam Efficient Splitting Rules Based on the Probabilities of Pre-assigned Intervals

S258 Andreas Hotho, Alexander Maedche, Steffen Staab Text Clustering Based on Good Aggregations

S224 J. Paetz Metric Rule Generation with Septic Shock Patient Data

S403 Stefan Ruping Incremental Learning with Support Vector Machines

S191 Zhiyong Liu, , Lei Xu RPCL-Based Local PCA Algorithm

S449 Rayid Ghani Combining Labeled and Unlabeled Data for Text Classification with a Large Number of Categories

S291 Nitesh Chawla, Steven Eschrich, Lawrence O. Hall Creating Ensembles of Classifiers

This page has been accessed

times since October 11, 2001.
Last modified: November 21, 2001.

ICDM '01
The 2001 IEEE International Conference on Data Mining

Sponsored by the IEEE Computer Society

Doubletree Hotel, San Jose, California, USA
November 29 - December 2, 2001

ICDM 2001 Program

S474	Osmar R. Zaiane, Mohammad El-Hajj, Paul Lu	Fast Parallel Association Rule Mining without Candidacy Generation
S467	Wolfgang Gaul, Lars Schmidt-Thieme	Mining Generalized Association Rules for Sequential and Path Data
S567	Honghua Dai	Inexact Field Learning: An Approach to Induce High Quality Rules from Low Quality Data
S445	Viviane Crestana Jensen, Nandit Soparkar	Heuristic Optimization for Decentralized Frequent Itemset Counting
S371	Viet Phan-Luong	The Representative Basis for Association Rules
S162	Fan-Chen Tseng, Ching-Chi Hsu, H. Chen	Mining Frequent Closed Itemsets with the Frequent Pattern List
S308	Hasan M. Jamil	Ad Hoc Association Rule Mining as SQL3 Queries
S257	Show-Jane Yen, Yue-Shi Lee	An Efficient Data Mining Technique for Discovering Interesting Sequential Patterns
S485	Carlotta Domeniconi, Dimitrios Gunopulos	Incremental Support Vector Machine Construction
S464	Sherri K. Harms, Jitender Deogun, Jamil Saquer, Tsegaye Tadesse	Discovering Representative Episodal Association Rules from Event Sequences Using Frequent Closed Episode Sets and Event Constraints

S361	Jie Chen, Haiying Li, Shiwei Tang	Association Rules Enhanced Classification of Underwater Acoustic Signal
S401	Samuel Steingold, Richard Wherry, Gregory Piatetsky-Shapiro	Measuring Real-Time Predictive Models
S278	Pascal Soucy, Guy W. Mineau	A Simple KNN Algorithm for Text Categorization
S513	Carlos Ordonez, Edward Omiecinski, N. Ezquerra	A Fast Algorithm to Cluster High Dimensional Basket Data
S130	D. Zhang, Q. Ha, M. Lu	Mining California Vital Statistics Data
S336	Fernando Alonso, ,Juan P. Caraça-Valente, Loïc Martínez, Cesar Montes	Discovering Similar Patterns for Characterizing Time Series in a Medical Domain
S332	Tadashi Nomoto, Yuji Matsumoto	An Experimental Comparison of Supervised and Unsupervised Approaches to Text Summarization
S338	Daniel Gillblad, Anders Holst	Dependency Derivation in Industrial Process Data
S240	Xiong Wang	a-Surface and Its Application to Mining Protein Data
S260	Petri Myllymaki, Tomi Silander, Henry Tirri, Pekka Uronen	Bayesian Data Mining on the Web with B-Course
S347	Bernard Zenko, Ljupco Todorovski, Saso Dzeroski	A Comparison of Stacking with Meta Decision Trees to Bagging, Boosting, and Stacking with other Methods

S505	X. Liang, and Y. Liang	Applications of Data Mining in Hydrology
S202	Tobias Scheffer, Christian Decomain, Stefan Wrobel	Mining the Web with Active Hidden Markov Models
S181	Gang LI, Fu Tong, Honghua Dai	Evolutionary Structure Learning Algorithm for Bayesian Network and Penalized Mutual Information Metric
S206	June-Suh Cho, Nabil R. Adam	Efficient Splitting Rules Based on the Probabilities of Pre-assigned Intervals
S258	Andreas Hotho, Alexander Maedche, Steffen Staab	Text Clustering Based on Good Aggregations
S224	J. Paetz	Metric Rule Generation with Septic Shock Patient Data
S403	Stefan Ruping	Incremental Learning with Support Vector Machines
S191	Zhiyong Liu, , Lei Xu	RPCL-Based Local PCA Algorithm
S449	Rayid Ghani	Combining Labeled and Unlabeled Data for Text Classification with a Large Number of Categories
S291	Nitesh Chawla, Steven Eschrich, Lawrence O. Hall	Creating Ensembles of Classifiers

ICDM '01 The 2001 IEEE International Conference on Data Mining

Sponsored by the IEEE Computer Society

Doubletree Hotel, San Jose, California, USA November 29 - December 2, 2001

ICDM 2001 Program

ICDM '01
The 2001 IEEE International Conference on Data Mining

Doubletree Hotel, San Jose, California, USA
November 29 - December 2, 2001