ICDM 2004 Tuesday November 2nd 2004
09:00-09:30am
Opening Remarks
09:30-10:30am Invited Talk (David Hand)
10:30-11:00am Break
11:00-12:30am Research Sessions (3 Parallel Tracks)
Track 1 (SVM) (3 Regular, 2 Short)
Jens Gregor and Zhenqiu Liu,
"A Bayesian Framework for Regularized SVM Parameter Estimation "
Gang Wu and Edward Chang,
"Aligning Boundary in Kernel Space for Learning Imbalanced Dataset "
David Gondek and Thomas Hofmann,
"Non-Redundant Data Clustering"
Ping Sun,
"Sparse Kernel Least Squares Classifier"
Francois Poulet,
"SVM and Graphical Algorithms: a Cooperative Approach"
Track 2 (Quality Assesment 1) (3
Regular, 2 Short)
Matjaz Kukar,
"Transduction and typicalness for quality assessment of individual classifications in machine learning and data mining "
Balasubramanian Shekar and Rajesh Natarajan,
"A Transaction-based Neighbourhood-driven Approach to Quantifying Interestingness of Association Rules "
Xingquan Zhu and Xindong Wu,
"Cost-guided Class Noise Handling for Effective Cost-sensitive Learning"
Sandeep Mane, Jaideep Srivastava, and San-Yih Hwang,
"Estimation of false negatives to predict the accuracy of the classifier"
Frans Coenen and Paul Leng,
"An Evaluation of Approaches to Classification Rule Selection"
Track 3 (Data Streams ) (2 Regular, 4
Short)
Xingquan Zhu and Xindong Wu,
"Dynamic Classifier Selection for Effective Mining from Noisy Data Streams"
Yun Chi, Haixun Wang, Philip Yu, and Richard Muntz,
"Moment: Maintaining Closed Frequent Itemsets over a Stream Sliding Window"
Wei Fan, Yi-an Huang, and Philip Yu,
"Decision Tree Evolution Using Limited Number of Labelled Items from Drifting Data Streams"
Jiong Yang and Wei Wang,
"AGILE: A General Approach to Detect Transitions in Evolving Data Streams"
Fang Chu, Yizhou Wang, and Carlo Zaniolo,
"An Adaptive Learning Approach for Noisy Data Streams"
Bi-Ru Dai, Ming-Syan Chen, Jen-Wei Huang, and Mi-Yen Yeh,
"Clustering on Demand for Multiple Data Streams"
12:30-02:00pm
Lunch
02:00-03:00pm
Invited Talk (Thorsten Joachims)
03:00-03:30pm
Break
03:30-05:30pm
Research Sessions (3 Parallel Tracks)
Track
1 (Frequent Sets 1 ) (3 Regular, 5 Short)
Francesco Bonchi and Claudio Lucchese,
"On Closed Constrained Frequent Pattern Mining"
Gosta Grahne and Jianfei Zhu,
"Mining Frequent Itemsets from Secondary Memory"
Heli Hiisilä and Ella Bingham,
"Dependencies between transcription factor binding sites: comparison between ICA, NMF, PLSA and frequent sets"
Yi Chen and Yu Guo Wang,
"Incremental Mining of Frequent XML Query Patterns"
Hwanjo Yu, Duane Searsmith, Xiaolei Li, and Jiawei Han,
"Scalable Construction of Topic Directory with Nonparametric Closed Termset Mining"
Gao Cong, Kian-Lee Tan, Anthony K. H. Tung, and Feng Pan,
"Mining Frequent Closed Patterns in Microarray Data"
Alexandre Termier, Marie-Christine Rousset, and Michele Sebag,
"Dryade: a new approach for discovering closed frequent trees in heterogeneous tree databases"
Ulrich Rückert, Lothar Richter, and Stefan Kramer,
"Quantitative Association Rules Based on Half Spaces: An Optimization Approach"
Track
2 (Clustering 1 ) (3 Regular, 5 Short)
Anjan Goswami, Ruoming Jin, and Gagan Agrawal,
"Fast and Exact Out-of-Core K-means Clustering"
Jianyong Wang and George Karypis,
"SUMMARY: Efficiently Summarizing Transactions for Clustering"
Christian Baumgartner, Karin Kailing, Hans-Peter Kriegel, Peer Kröger, and Claudia Plant,
"Subspace Selection for Clustering High-Dimensional Data"
Dan Simovici, Namita Singla, and Michael Kuperberg,
"Metric Incremental Clustering of Nominal Data"
Christoph Eick, Nidal Zeidat, and Ricardo Vilalta,
"Using Representative-Based Clustering for Nearest Neighbor Dataset Editing"
Yi-Dong Shen, Zhiyong Shen, Shiming Zhang, and Qiang Yang,
"Cluster Cores-based Clustering for High Dimensional Data"
Jinze Liu, Karl Strohmaier, and Wei Wang,
"Revealing True Subspace Clusters in High Dimensions"
Hyungil Kim, Juntae Kim, and Jonathan Herlocker,
"Feature-Based Prediction of Unknown Preferences for Nearest-Neighbor Collaborative Filtering"
Track
3 (Web and Text Mining ) (2 Regular, 7 Short)
Laurence Park and Kotagiri Ramamohanarao,
"Hybrid pre-query term expansion using Latent Semantic Analysis"
Tao Liu, Zheng Chen, Benyu Zhang, Wei-ying Ma, and Gongyi Wu,
"Improving Text Classification using Local Latent Semantic Indexing"
Shalendra Chhabra, William Yerazunis, and Christian Siefkes,
"Spam Filtering using a Markov Random Field Model with Variable Weighting Schemas"
David Gleich and Leonid Zhukov,
"SVD based Term Suggestion and Ranking System"
Véronique Ventos, Henry Soldano, and Thibaut Lamadon
"Alpha Galois Lattices"
Juan Velasquez, Alejandro Bassi, Hiroshi Yasuda, and Terumasa Aoki,
"Mining web data to create online navigation recommendations"
Harry Zhang and Jiang Su,
"Learning Conditional Independence Trees for Ranking"
Nenad Stojanovic,
"On Ranking Refinements in the step-by-step Searching through a Product Catalogue;
Jian-Tao Sun, Zheng Chen, Hua-Jun Zeng, Yu-Chang Lu, Chun-Yi Shi, and Wei-Ying Ma,
"Supervised Latent Semantic Indexing for Document Categorization"
ICDM 2004 Wednesday November 3rd 2004
09:00-10:00am
Invited Talk (Wray Buntine)
10:00-10:30am Break
10:30-12:00am Research Sessions (3 Parallel Tracks)
Track
1 (Bayes ) (2 Regular, 4 Short)
Xiaoyong Chai, Lin Deng, Qiang Yang, and Charles X. Ling,
"Test-Cost Sensitive Naive Bayes Classification"
Jun Zhang and Vasant Honavar,
"Learning Concise and Accurate Naive Bayes Classifiers From Attribute Value Taxonomies and Data"
Shengli Sheng,
"Learning Weighted Naive Bayes with Accurate Ranking"
David Lindsay and Sian Cox,
"Improving the Reliability of Decision Tree and Naive Bayes Learners"
Margaret Dunham, Yu Meng, and Jie Huang,
"Extensible Markov Model"
Da Meng, Krishnamoorthy Sivakumar and Hillol Kargupta,
"Privacy Sensitive Bayesian Network Parameter Learning"
Track 2 (Quality Assesment 2 ) (2
Regular, 2 Short)
Todd Olsen, Chris Giannella, Kun Liu, and Hillol Kargupta,
"Communication Efficient Construction of Decision Trees Over Heterogeneously Distributed Data"
Karlton Sequeira and Mohammed Zaki,
"SCHISM: A New Approach for Interesting Subspace Mining"
Tianyi Jiang and Alexander Tuzhilin,
"Divide and Prosper: Comparing Models of Customer Behavior"
Ning Zhong, Mingxin Huang, Chunnian Liu, and Y.Y. Yao,
"Relational Peculiarity Oriented Data Mining"
Track 3 (Time Data ) (2 Regular, 4 Short)
Niina Haiminen and Aristides Gionis,
"Unimodal segmentation of sequences;
Mikhail Atallah, Robert Gwadera and Wojciech Szpankowski,
"Detection of Significant Sets of Episodes in Event Sequences"
Beum-Seuk Lee, Trevor Martin, Nick Clarke, Basim Majeed, and Detlef Nauck,
"Dynamic Daily-living Patterns and Association Analyses in Tele-care Systems"
Tao Li and Sheng Ma,
"Mining Temporal Patterns Without Predefined Time Windows"
Xi Ma, HweeHwa Pang, and Kian-Lee Tan,
"Finding Constrained Frequent Episodes Using Minimal Occurrences"
Chih Lai and Nga Nguyen,
"Predicting Density-Based Spatial Clusters Over Time"
12:30-02:00pm
Lunch
ICDM 2004 Thursday November 4th 2004
09:00-10:00am
Invited Talk (Ming Li)
10:00-10:30am Break
10:30-12:30am Research Sessions (3 Parallel Tracks)
Track 1 (Structured Data ) (2 Regular,
6 Short)
Stefan Brecheisen, Hans-Peter Kriegel, and Martin Pfeifle,
"Efficient Density-Based Clustering of Complex Objects"
Jennifer Neville and David Jensen,
"Dependency Networks for Relational Data"
Michihiro Kuramochi and George Karypis
" GREW---A Scalable Frequent Subgraph Discovery Algorithm
"
Alexessander Alves, Rui Camacho, and Eugenio Oliveira
" Discovery of Functional Relationships in Multi-relational Data
using Inductive
Logic Programming "
Akihiro Inokuchi
" Mining Generalized Substructures from a Set of Labeled
Graphs"
Hillol Kargupta and Haimonti Dutta
"Orthogonal Decision Trees"
Amanda Clare, Hugh Williams, and Nicholas Lester
"Scalable Multi-Relational Association Mining"
Dawit Seid and Sharad Mehrotra
"Efficient Relationship Pattern Mining using Multi-relational
Iceberg-Cubes"
Track 2 (Ensembles ) (3 Regular, 5 Short)
Grigoris Karakoulas and Ruslan Salakhutdinov
" Semi-Supervised Mixture-of-Experts Classification "
Gui-Rong Xue, Dou Shen, Qiang Yang, Hua-Jun Zeng, Zheng Chen, and
Wei-Ying Ma
" IRC: An Iterative Reinforcement Categorization Algorithm for
Interrelated Web Objects "
Feng Zhang and Danieal Apley
"A Polygonal Line Algorithm based Nonlinear"
Andrei Turinsky and Robert Grossman
"A Greedy Algorithm for Selecting Models in Ensembles"
Stephan Bloehdorn and Andreas Hotho
"Text Classification by BoostingWeak Learners based on Terms and
Concepts"
Chenyong Hu, Benyu Zhang, Shuicheng Yan, Qiang Yang, Zheng Chen, and
Weiying Ma
"Mining Ratio Rules Via Principal Sparse Non-Negative Matrix
Factorization"
Pierre Geurts, Ibtissam El Khayat, and Guy Leduc
"A machine learning approach to improve congestion control over
wireless computer
networks"
Michael Baranski and Jürgen Voss
"Detecting Patterns of Appliances from Total Load Data Using a
Dynamic Programming
Approach"
Track 3 (Ensembles ) (3 Regular, 5 Short)
Pei Sun and Sanjay Chawla
"On Local Spatial Outliers"
Jaideep Vaidya and Chris Clifton
"Privacy-Preserving Outlier Detection"
Ke Wang, Philip Yu, and Sourav Chakraborty
"Bottom-up generalization: A data mining solution to privacy
protection"
Dongmei Ren
"RDF: A Density-based Outlier Detection using vertical Data
Representation"
Amol Ghoting, Matthew Otey, and Srinivasan Parthasarathy
"LOADED: Link-based Outlier and Anomaly Detection in Evolving Data
Sets"
Jia-Yu Pan, Hyungjeong Yang, and Christos Faloutsos
"MMSS: Multi-modal Story-oriented Video Summarization"
Antonio Gulli and Paolo Ferragina
"The Anatomy of a Hierarchical Clustering Engine for Web-page
Snippets"
Hamad Alhamady and Kotagiri Rao
"Using Emerging Patterns and Decision Trees in Rare-class
Classification"
12:30-02:00pm
Lunch
01:15-02:00pm
ICDM Business Meeting (in the same room as the Panel Discussion)
02:00-03:00pm Panel
03:00-03:30pm Break
03:30-05:30pm Research Sessions (3 Parallel Tracks)
Track 1 (Feature Selection ) (2 Regular,
7 Short)
Dae-Ki Kang, Adrian Silvescu, Jun Zhang, and Vasant Honavar
"Generation of Attribute Value Taxonomies from Data and Their Use
in Data-Driven
Construction of Accurate and Compact Classifiers"
Tak-Lam Wong and Wai Lam
"A Probabilistic Approach for Adapting Information Extraction
Wrappers and
Discovering New Attributes"
Andrew Arnt and Shlomo Zilberstein
"Attribute Measurement Policies for Cost-effective
Classification"
Yue Huang, Paul McCullagh, Norman Black, and Roy Harper
"Feature Selection via Supervised Model Construction"
Toshihiro Kamishima and Shotaro Akaho
"Filling-in Missing Objects in Orders"
Emilio Carrizosa, Belen Martin-Barragan, and Dolores Romero Morales
"A biobjective model to select features with good classification
quality and low cost"
Sameep Mehta, Srinivasan Parthasarathy, and Hui Yang
"Correlation Preserving Discretization"
Cheong Hee Park and Haesun Park
"A Comparative Study of Linear and Nonlinear Feature Extraction
Methods"
Prem Melville, Maytal Saar-Tsechansky, Foster Provost, and Raymond
Mooney
"Active Feature-Value Acquisition for Classifier
Induction"
Track 2 (Clustering 2 ) (4 Regular, 3 Short)
Christian Böhm, Karin Kailing, Hans-Peter Kriegel, and Peer Kröger
"Density Connected Clustering with Local Subspace
Preferences"
Zheng Huang, Lei Chen, Jin-Yi Cai, Deborah Gross, David Musicant, Raghu
Ramakrishnan, and James J. Schauer
"Mass Spectrum Labeling: Theory and Practice"
Steffen Bickel and Tobias Scheffer
"Multi-View Clustering"
Alexander Topchy, Martin Law, Anil Jain, and Ana Fred
"Analysis of Consensus Partition in Cluster Ensemble"
Eduardo Hruschka, Leandro Castro, and Ricardo Campello
"Evolutionary Algorithms for Clustering Gene-Expression
Data"
Marko Salmenkivi
"Evaluating Attraction in Spatial Point Patterns with an
Application in the Field of
Cultural History"
Daoying Ma and Aidong Zhang
"An Adaptive Density-Based Clustering Algorithm for Spatial
Database with Noise"
Track 3 (Frequent Sets ) (3 Regular, 4 Short)
T. Y. Lin
"Mining Associations by Solving Integral Linear
Inequalities"
Antonino Staiano, Roberto Tagliaferri, Giancarlo Raiconi, Giuseppe
Longo, Gennaro
Miele, and Diego Di Bernardo
"Probabilistic Principal Surfaces for Yeast Gene Microarray Data
Mining"
Fadi Thabtah, Peter Cowling, and Yonghong Peng
"MMAC: A New Multi-class, Multi-label Associative Classification
Approach"
Yiqiu Han and Wai Lam
"Query-Driven Support Pattern Discovery for Classification
Learning"
Jianping Zhang, Eric Bloedorn, Lowell Rosen, and Daniel Venese
"Learning Rules from Highly Unbalanced Data Sets"
Björn Bringmann
"Matching in Frequent Tree Discovery"
Mehmet Kaya and Reda Alhajj
"Integrating Multi-Objective Genetic Algorithms into Clustering
for Fuzzy
Association Rules Mining"