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 BibTeX

Carl Mooney, John F. Roddick:
Mining Relationships Between Interacting Episodes.
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Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh:
Making Time-Series Classification More Accurate Using Learned Constraints.
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Hansheng Lei:
GRM: A New Model for Clustering Linear Sequences.
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Martin H. C. Law, Nan Zhang, Anil K. Jain:
Nonlinear Manifold Learning for Data Stream.
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Wai Lam, Tak-Lam Wong:
Text Mining from Site Invariant and Dependent Features for Information Extraction Knowledge Adaptation.
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Parvathi Chundi, Daniel J. Rosenkrantz:
Constructing Time Decompositions for Analyzing Time-Stamped Documents.
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Peg Howland, Haesun Park:
Equivalence of Several Two-Stage Methods for Linear Discriminant Analysis.
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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.
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Martin Ester, Xiang Zhang:
A Top-Down Method for Mining Most-Specific Frequent Patterns in Biological Sequences.
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Hans-Peter Kriegel, Peer Kröger, Alexey Pryakhin, Matthias Schubert:
Using Support Vector Machines for Classifying Large Sets of Multi-Represented Objects.
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Hyuk Cho, Inderjit S. Dhillon, Yuqiang Guan, Suvrit Sra:
Minimum Sum-Squared Residue Co-Clustering of Gene Expression Data.
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Daniel Boley, Dongwei Cao:
Training Support Vector Machines Using Adaptive Clustering.
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Oliver Dain, Robert Cunningham, Stephen Boyer:
IREP++, A Faster Rule Learning Algorithm.
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Chetan Gupta, Robert L. Grossman:
GenIc: A Single-Pass Generalized Incremental Algorithm for Clustering.
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Jie Chi, Mehmet Koyutürk, Ananth Grama:
Conquest: A Distributed Tool for Constructing Summaries of High-Dimensional Discrete Attribute Data Sets.
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Guichong Li, Howard J. Hamilton:
Basic Association Rules.
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Alípio Jorge:
Hierarchical Clustering for Thematic Browsing and Summarization of Large Sets of Association Rules.
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Ronald K. Pearson, Tom Zylkin, James S. Schwaber, Gregory E. Gonye:
Analytical Evaluation of Clustering Results Using Computational Negative Controls.
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Richard Nock, Frank Nielsen:
An Abstract Weighting Framework for Clustering Algorithms.
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Aysel Ozgur, Pang-Ning Tan, Vipin Kumar:
RBA: An Integrated Framework for Regression based on Association Rules.
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Wenliang Du, Yunghsiang S. Han, Shigang Chen:
Privacy-Preserving Multivariate Statistical Analysis: Linear Regression and Classification.
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Arindam Banerjee, Srujana Merugu, Inderjit S. Dhillon, Joydeep Ghosh:
Clustering with Bregman Divergences.
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Peer Kröger, Hans-Peter Kriegel, Karin Kailing:
Density-Connected Subspace Clustering for High-Dimensional Data.
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Qiang Du, Xiaoqiang Wang:
Tesselation and Clustering by Mixture Models and Their Parallel Implementations.
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Ming-Syan Chen, Kun-Ta Chuang:
Clustering Categorical Data Using the Correlated-Force Ensemble.
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Hui Xiong, Michael Steinbach, Pang-Ning Tan, Vipin Kumar:
HICAP: Hierarchical Clustering with Pattern Preservation.
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Deepak Agrawal, Daryl Pregibon:
Enhancing Communities of Interest Using Bayesian Stochastic Blockmodels.
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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.
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Hung-Yu Kao, Jan-Ming Ho, Ming-Syan Chen:
DOMISA: DOM-Based Information Space Adsorption of Web Information Hierarchy Mining.
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Mahesh V. Joshi, Vipin Kumar:
CREDOS: Classification Using Ripple Down Structure (A Case for Rare Classes).
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Sugato Basu, Arindam Banerjee, Raymond J. Mooney:
Active Semi-Supervision for Pairwise Constrained Clustering.
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Michihiro Kuramochi, George Karypis:
Finding Frequent Patterns in a Large Sparse Graph.
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Nobuhisa Ueda, Kiyoko F. Aoki, Hiroshi Mamitsuka:
A General Probabilistic Framework for Mining Labeled Ordered Trees.
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Ashok N. Srivastava:
Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data.
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Alexander P. Topchy, Anil K. Jain, William F. Punch:
A Mixture Model for Clustering Ensembles.
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Ron Kohavi, Rajesh Parekh:
Visualizing RFM Segmentation.
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Stefan Brecheisen, Hans-Peter Kriegel, Peer Kröger, Martin Pfeifle:
Visually Mining through Cluster Hierarchies.
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Amit Mandvikar, Huan Liu:
Class-Specific Ensembles for Active Learning.
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Reinhard Rapp:
Mining Text for Word Senses Using Independent Component Analysis.
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Anne Denton, William Perrizo:
A Kernel-Based Semi-Naïve Bayesian Classifier Using P-Trees.
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Jianyong Wang, George Karypis:
BAMBOO: Accelerating Closed Itemset Mining by Deeply Pushing the Length-Decreasing Support Constraint.
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Yihua Liao, V. Rao Vemuri, Alejandro Pasos:
A General Framework for Adaptive Anomaly Detection with Evolving Connectionist Systems.
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Deepayan Chakrabarti, Yiping Zhan, Christos Faloutsos:
R-MAT: A Recursive Model for Graph Mining.
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Yiqiu Han, Wai Lam:
Lazy Learning by Scanning Memory Image Lattice.
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V. Paul Pauca, Farial Shahnaz, Michael W. Berry, Robert J. Plemmons:
Text Mining Using Non-Negative Matrix Factorizations.
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Wei Fan, Yi-an Huang, Haixun Wang, Philip S. Yu:
Active Mining of Data Streams.
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Ata Kabán, Ella Bingham, T. Hirsimäki:
Learning to Read Between the Lines: The Aspect Bernoulli Model.
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Yiqiu Han, Wai Lam:
Exploiting Hierarchical Domain Values in Classification Learning.
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Tao Li, Sheng Ma:
IFD: Iterative Feature and Data Clustering.
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Lifang Gu, Rohan A. Baxter:
Adaptive Filtering for Efficient Record Linkage.
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Hong Yao, Howard J. Hamilton, Cory J. Butz:
A Foundational Approach to Mining Itemset Utilities from Databases.
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Gang Li, Honghua Dai:
The Discovery of Generalized Causal Models with Mixed Variables Using MML Criterion.
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Byung-Hoon Park, George Ostrouchov, Nagiza F. Samatova, Al Geist:
Reservoir-Based Random Sampling with Replacement from Data Stream.
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Chris H. Q. Ding, Xiaofeng He:
Principal Component Analysis and Effective K-Means Clustering.
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Daniel Barbará, Carlotta Domeniconi, Ning Kang:
Classifying Documents Without Labels.
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Hyunsoo Kim, Haesun Park:
Data Reduction in Support Vector Machines by a Kernelized Ionic Interaction Model.
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Sathyakama Sandilya, R. Bharat Rao:
Continuous-Time Bayesian Modeling of Clinical Data.
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Carlotta Domeniconi, Dimitris Papadopoulos, Dimitrios Gunopulos, Sheng Ma:
Subspace Clustering of High Dimensional Data.
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Jaideep Vaidya, Chris Clifton:
Privacy Preserving Naïve Bayes Classifier for Vertically Partitioned Data.
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Wei-Guang Teng, Ming-Syan Chen, Philip S. Yu:
Resource-Aware Mining with Variable Granularities in Data Streams.
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Michael C. Burl:
Mining Patters of Activity from Video Data.
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