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ORCID4th SDM 2004: Orlando, Florida, USA
- Michael W. Berry, Umeshwar Dayal, Chandrika Kamath, David B. Skillicorn:
Proceedings of the Fourth SIAM International Conference on Data Mining, Lake Buena Vista, Florida, USA, April 22-24, 2004. SIAM 2004, ISBN 978-0-89871-568-2 - Carl Mooney
, John F. Roddick:
Mining Relationships Between Interacting Episodes. 1-10 - Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh:
Making Time-Series Classification More Accurate Using Learned Constraints. 11-22 - Hansheng Lei:
GRM: A New Model for Clustering Linear Sequences. 23-32 - Martin H. C. Law, Nan Zhang, Anil K. Jain:
Nonlinear Manifold Learning for Data Stream. 33-44 - Wai Lam, Tak-Lam Wong:
Text Mining from Site Invariant and Dependent Features for Information Extraction Knowledge Adaptation. 45-56 - Parvathi Chundi, Daniel J. Rosenkrantz:
Constructing Time Decompositions for Analyzing Time-Stamped Documents. 57-68 - Peg Howland, Haesun Park:
Equivalence of Several Two-Stage Methods for Linear Discriminant Analysis. 69-77 - 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. 78-89 - Martin Ester, Xiang Zhang:
A Top-Down Method for Mining Most-Specific Frequent Patterns in Biological Sequences. 90-101 - Hans-Peter Kriegel, Peer Kröger, Alexey Pryakhin, Matthias Schubert:
Using Support Vector Machines for Classifying Large Sets of Multi-Represented Objects. 102-113 - Hyuk Cho, Inderjit S. Dhillon, Yuqiang Guan, Suvrit Sra:
Minimum Sum-Squared Residue Co-Clustering of Gene Expression Data. 114-125 - Daniel Boley, Dongwei Cao:
Training Support Vector Machines Using Adaptive Clustering. 126-137 - Oliver Dain, Robert K. Cunningham, Stephen Boyer:
IREP++, A Faster Rule Learning Algorithm. 138-146 - Chetan Gupta, Robert L. Grossman:
GenIc: A Single-Pass Generalized Incremental Algorithm for Clustering. 147-153 - Jie Chi, Mehmet Koyutürk, Ananth Grama:
Conquest: A Distributed Tool for Constructing Summaries of High-Dimensional Discrete Attribute Data Sets. 154-165 - Guichong Li, Howard J. Hamilton:
Basic Association Rules. 166-177 - Alípio Jorge:
Hierarchical Clustering for Thematic Browsing and Summarization of Large Sets of Association Rules. 178-187 - Ronald K. Pearson, Tom Zylkin, James S. Schwaber, Gregory E. Gonye:
Analytical Evaluation of Clustering Results Using Computational Negative Controls. 188-199 - Richard Nock, Frank Nielsen:
An Abstract Weighting Framework for Clustering Algorithms. 200-209 - Aysel Ozgur, Pang-Ning Tan, Vipin Kumar:
RBA: An Integrated Framework for Regression based on Association Rules. 210-221 - Wenliang Du, Yunghsiang S. Han, Shigang Chen:
Privacy-Preserving Multivariate Statistical Analysis: Linear Regression and Classification. 222-233 - Arindam Banerjee, Srujana Merugu, Inderjit S. Dhillon, Joydeep Ghosh:
Clustering with Bregman Divergences. 234-245 - Karin Kailing, Hans-Peter Kriegel, Peer Kröger:
Density-Connected Subspace Clustering for High-Dimensional Data. 246-256 - Qiang Du, Xiaoqiang Wang:
Tesselation and Clustering by Mixture Models and Their Parallel Implementations. 257-268 - Ming-Syan Chen, Kun-Ta Chuang:
Clustering Categorical Data Using the Correlated-Force Ensemble. 269-278 - Hui Xiong, Michael S. Steinbach, Pang-Ning Tan, Vipin Kumar:
HICAP: Hierarchical Clustering with Pattern Preservation. 279-290 - Deepak Agrawal, Daryl Pregibon:
Enhancing Communities of Interest Using Bayesian Stochastic Blockmodels. 291-299 - 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. 300-311 - Hung-Yu Kao, Jan-Ming Ho, Ming-Syan Chen:
DOMISA: DOM-Based Information Space Adsorption of Web Information Hierarchy Mining. 312-320 - Mahesh V. Joshi, Vipin Kumar:
CREDOS: Classification Using Ripple Down Structure (A Case for Rare Classes). 321-332 - Sugato Basu, Arindam Banerjee, Raymond J. Mooney:
Active Semi-Supervision for Pairwise Constrained Clustering. 333-344 - Michihiro Kuramochi, George Karypis:
Finding Frequent Patterns in a Large Sparse Graph. 345-356 - Nobuhisa Ueda, Kiyoko F. Aoki, Hiroshi Mamitsuka:
A General Probabilistic Framework for Mining Labeled Ordered Trees. 357-368 - Ashok N. Srivastava:
Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data. 369-378 - Alexander P. Topchy, Anil K. Jain, William F. Punch:
A Mixture Model for Clustering Ensembles. 379-390 - Ron Kohavi, Rajesh Parekh:
Visualizing RFM Segmentation. 391-399 - Stefan Brecheisen, Hans-Peter Kriegel, Peer Kröger, Martin Pfeifle:
Visually Mining through Cluster Hierarchies. 400-411 - Amit Mandvikar, Huan Liu:
Class-Specific Ensembles for Active Learning. 412-421 - Reinhard Rapp:
Mining Text for Word Senses Using Independent Component Analysis. 422-426 - Anne Denton, William Perrizo:
A Kernel-Based Semi-Naïve Bayesian Classifier Using P-Trees. 427-431 - Jianyong Wang, George Karypis:
BAMBOO: Accelerating Closed Itemset Mining by Deeply Pushing the Length-Decreasing Support Constraint. 432-436 - Yihua Liao, V. Rao Vemuri, Alejandro Pasos:
A General Framework for Adaptive Anomaly Detection with Evolving Connectionist Systems. 437-441 - Deepayan Chakrabarti, Yiping Zhan, Christos Faloutsos:
R-MAT: A Recursive Model for Graph Mining. 442-446 - Yiqiu Han, Wai Lam:
Lazy Learning by Scanning Memory Image Lattice. 447-451 - V. Paul Pauca, Farial Shahnaz, Michael W. Berry, Robert J. Plemmons:
Text Mining Using Non-Negative Matrix Factorizations. 452-456 - Wei Fan, Yi-an Huang, Haixun Wang, Philip S. Yu:
Active Mining of Data Streams. 457-461 - Ata Kabán, Ella Bingham, T. Hirsimäki:
Learning to Read Between the Lines: The Aspect Bernoulli Model. 462-466 - Yiqiu Han, Wai Lam:
Exploiting Hierarchical Domain Values in Classification Learning. 467-471 - Tao Li, Sheng Ma:
IFD: Iterative Feature and Data Clustering. 472-476 - Lifang Gu, Rohan A. Baxter:
Adaptive Filtering for Efficient Record Linkage. 477-481 - Hong Yao, Howard J. Hamilton, Cory J. Butz:
A Foundational Approach to Mining Itemset Utilities from Databases. 482-486 - Gang Li, Honghua Dai:
The Discovery of Generalized Causal Models with Mixed Variables Using MML Criterion. 487-491 - Byung-Hoon Park, George Ostrouchov, Nagiza F. Samatova, Al Geist:
Reservoir-Based Random Sampling with Replacement from Data Stream. 492-496 - Chris H. Q. Ding, Xiaofeng He:
Principal Component Analysis and Effective K-Means Clustering. 497-501 - Daniel Barbará, Carlotta Domeniconi, Ning Kang:
Classifying Documents Without Labels. 502-506 - Hyunsoo Kim, Haesun Park:
Data Reduction in Support Vector Machines by a Kernelized Ionic Interaction Model. 507-511 - Sathyakama Sandilya, R. Bharat Rao:
Continuous-Time Bayesian Modeling of Clinical Data. 512-516 - Carlotta Domeniconi, Dimitris Papadopoulos, Dimitrios Gunopulos, Sheng Ma:
Subspace Clustering of High Dimensional Data. 517-521 - Jaideep Vaidya, Chris Clifton:
Privacy Preserving Naïve Bayes Classifier for Vertically Partitioned Data. 522-526 - Wei-Guang Teng, Ming-Syan Chen, Philip S. Yu:
Resource-Aware Mining with Variable Granularities in Data Streams. 527-531 - Michael C. Burl:
Mining Patters of Activity from Video Data. 532-536
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