4. SDM 2004: Orlando, Florida, USA
Michael W. Berry, Umeshwar Dayal, Chandrika Kamath, David B. Skillicorn (Eds.): Proceedings of the Fourth SIAM International Conference on Data Mining, Lake Buena Vista, Florida, USA, April 22-24, 2004. SIAM 2004 ISBN 0-89871-568-7- Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh: Making Time-Series Classification More Accurate Using Learned Constraints.
- Hansheng Lei: GRM: A New Model for Clustering Linear Sequences.
- Wai Lam, Tak-Lam Wong: Text Mining from Site Invariant and Dependent Features for Information Extraction Knowledge Adaptation.
- Parvathi Chundi, Daniel J. Rosenkrantz: Constructing Time Decompositions for Analyzing Time-Stamped Documents.
- Peg Howland, Haesun Park: Equivalence of Several Two-Stage Methods for Linear Discriminant Analysis.
- Hui Xiong, Shashi Shekhar, Yan Huang, Vipin Kumar, Xiaobin Ma, Jin Soung Yoo: A Framework for Discovering Co-Location Patterns in Data Sets with Extended Spatial Objects.
- Martin Ester, Xiang Zhang: A Top-Down Method for Mining Most-Specific Frequent Patterns in Biological Sequences.
- Hans-Peter Kriegel, Peer Kröger, Alexey Pryakhin, Matthias Schubert: Using Support Vector Machines for Classifying Large Sets of Multi-Represented Objects.
- Hyuk Cho, Inderjit S. Dhillon, Yuqiang Guan, Suvrit Sra: Minimum Sum-Squared Residue Co-Clustering of Gene Expression Data.
- Chetan Gupta, Robert L. Grossman: GenIc: A Single-Pass Generalized Incremental Algorithm for Clustering.
- Jie Chi, Mehmet Koyutürk, Ananth Grama: Conquest: A Distributed Tool for Constructing Summaries of High-Dimensional Discrete Attribute Data Sets.
- Alípio Jorge: Hierarchical Clustering for Thematic Browsing and Summarization of Large Sets of Association Rules.
- Ronald K. Pearson, Tom Zylkin, James S. Schwaber, Gregory E. Gonye: Analytical Evaluation of Clustering Results Using Computational Negative Controls.
- Aysel Ozgur, Pang-Ning Tan, Vipin Kumar: RBA: An Integrated Framework for Regression based on Association Rules.
- Wenliang Du, Yunghsiang S. Han, Shigang Chen: Privacy-Preserving Multivariate Statistical Analysis: Linear Regression and Classification.
- Arindam Banerjee, Srujana Merugu, Inderjit S. Dhillon, Joydeep Ghosh: Clustering with Bregman Divergences.
- Peer Kröger, Hans-Peter Kriegel, Karin Kailing: Density-Connected Subspace Clustering for High-Dimensional Data.
- Qiang Du, Xiaoqiang Wang: Tesselation and Clustering by Mixture Models and Their Parallel Implementations.
- Hui Xiong, Michael Steinbach, Pang-Ning Tan, Vipin Kumar: HICAP: Hierarchical Clustering with Pattern Preservation.
- Deepak Agrawal, Daryl Pregibon: Enhancing Communities of Interest Using Bayesian Stochastic Blockmodels.
- Hillol Kargupta, Ruchita Bhargava, Kun Liu, Michael Powers, Patrick Blair, Samuel Bushra, James Dull, Kakali Sarkar, Martin Klein, Mitesh Vasa, David Handy: VEDAS: A Mobile and Distributed Data Stream Mining System for Real-Time Vehicle Monitoring.
- Hung-Yu Kao, Jan-Ming Ho, Ming-Syan Chen: DOMISA: DOM-Based Information Space Adsorption of Web Information Hierarchy Mining.
- Mahesh V. Joshi, Vipin Kumar: CREDOS: Classification Using Ripple Down Structure (A Case for Rare Classes).
- Sugato Basu, Arindam Banerjee, Raymond J. Mooney: Active Semi-Supervision for Pairwise Constrained Clustering.
- Nobuhisa Ueda, Kiyoko F. Aoki, Hiroshi Mamitsuka: A General Probabilistic Framework for Mining Labeled Ordered Trees.
- Ashok N. Srivastava: Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data.
- Stefan Brecheisen, Hans-Peter Kriegel, Peer Kröger, Martin Pfeifle: Visually Mining through Cluster Hierarchies.
- Reinhard Rapp: Mining Text for Word Senses Using Independent Component Analysis.
- Jianyong Wang, George Karypis: BAMBOO: Accelerating Closed Itemset Mining by Deeply Pushing the Length-Decreasing Support Constraint.
- Yihua Liao, V. Rao Vemuri, Alejandro Pasos: A General Framework for Adaptive Anomaly Detection with Evolving Connectionist Systems.
- V. Paul Pauca, Farial Shahnaz, Michael W. Berry, Robert J. Plemmons: Text Mining Using Non-Negative Matrix Factorizations.
- Ata Kabán, Ella Bingham, T. Hirsimäki: Learning to Read Between the Lines: The Aspect Bernoulli Model.
- Hong Yao, Howard J. Hamilton, Cory J. Butz: A Foundational Approach to Mining Itemset Utilities from Databases.
- Gang Li, Honghua Dai: The Discovery of Generalized Causal Models with Mixed Variables Using MML Criterion.
- Byung-Hoon Park, George Ostrouchov, Nagiza F. Samatova, Al Geist: Reservoir-Based Random Sampling with Replacement from Data Stream.
- Hyunsoo Kim, Haesun Park: Data Reduction in Support Vector Machines by a Kernelized Ionic Interaction Model.
- Carlotta Domeniconi, Dimitris Papadopoulos, Dimitrios Gunopulos, Sheng Ma: Subspace Clustering of High Dimensional Data.
- Jaideep Vaidya, Chris Clifton: Privacy Preserving Naïve Bayes Classifier for Vertically Partitioned Data.
- Wei-Guang Teng, Ming-Syan Chen, Philip S. Yu: Resource-Aware Mining with Variable Granularities in Data Streams.
- Michael C. Burl: Mining Patters of Activity from Video Data.
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last updated on 2013-06-18T211851 by the dblp team