ICDM '01
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November 29 |
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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 |
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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 |
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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
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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 |
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 |
S306
Wai-Ho Au, Keith C.C. Chan Classification with Degree of Membership: A Fuzzy Approach |
8 |
S522
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S398
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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 |
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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
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S311
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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 |
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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
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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 |
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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
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S504
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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 |
S161
Eamonn Keogh, Selina Chu, David Hart, Michael Pazzani An Online Algorithm for Segmenting Time Series |
S272 |
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
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24 |
S316
Virginia Wheway Using Boosting to Simplify Classification Models |
S498
Michihiro Kuramochi, George Karypis Frequent Subgraph Discovery |
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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:
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5:00 | Adjourn |
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 |
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 |