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ORCID6th SDM 2006: Bethesda, MD, USA
- Joydeep Ghosh, Diane Lambert, David B. Skillicorn, Jaideep Srivastava:
Proceedings of the Sixth SIAM International Conference on Data Mining, April 20-22, 2006, Bethesda, MD, USA. SIAM 2006, ISBN 978-0-89871-611-5
Theory
- Alan Herschtal, Bhavani Raskutti, Peter K. Campbell:
Area Under ROC Optimisation using a Ramp Approximation. 1-11 - Chih-Ming Hsu, Ming-Syan Chen:
On the Necessary and Sufficient Conditions of a Meaningful Distance Function for High Dimensional Data Space. 12-23 - Jieping Ye, Tao Xiong, Ravi Janardan:
CPM: A Covariance-preserving Projection Method. 24-34 - Edwin P. D. Pednault:
Transform Regression and the Kolmogorov Superposition Theorem. 35-46
Enterprise Applications
- Indrajit Bhattacharya, Lise Getoor:
A Latent Dirichlet Model for Unsupervised Entity Resolution. 47-58 - Sheng Zhang, James Ford, Fillia Makedon:
Deriving Private Information from Randomly Perturbed Ratings. 59-69 - Christopher P. Diehl, Lise Getoor, Galileo Namata:
Name Reference Resolution in Organizational Email Archives. 70-81 - Michael C. Burl, Dennis DeCoste, Brian L. Enke, Dominic Mazzoni, William J. Merline, Lucas Scharenbroich:
Automated Knowledge Discovery from Simulators. 82-93
Anomalies and Outliers
- Pei Sun, Sanjay Chawla, Bavani Arunasalam:
Mining for Outliers in Sequential Databases. 94-105 - Chao Liu, Xifeng Yan, Jiawei Han:
Mining Control Flow Abnormality for Logic Error Isolation. 106-117 - György J. Simon, Hui Xiong, Eric Eilertson, Vipin Kumar:
Scan Detection: A Data Mining Approach. 118-129
Network Relations
- Carsten Riggelsen:
Learning Bayesian Networks from Incomplete Data: An Efficient Method for Generating Approximate Predictive Distributions. 130-140 - Facundo Bromberg
, Dimitris Margaritis, Vasant G. Honavar:
Efficient Markov Network Structure Discovery using Independence Tests. 141-152 - Souptik Datta, Chris Giannella, Hillol Kargupta:
K-Means Clustering Over a Large, Dynamic Network. 153-164
Prototype Generation
- Benjamin J. Anderson, Deborah S. Gross, David R. Musicant, Anna M. Ritz, Thomas G. Smith, Leah E. Steinberg:
Adapting K-Medians to Generate Normalized Cluster Centers. 165-175 - Hans-Peter Kriegel, Matthias Schubert:
Advanced Prototype Machines: Exploring Prototypes for Classification. 176-187 - Andrea Tagarelli, Sergio Greco:
Toward Semantic XML Clustering. 188-199
Applications in Biology
- Xiaohua Hu, Xiaodan Zhang, Illhoi Yoo, Yanqing Zhang:
A Semantic Approach for Mining Hidden Links from Complementary and Non-interactive Biomedical Literature. 200-209 - Charu C. Aggarwal:
Representation is Everything: Towards Efficient and Adaptable Similarity Measures for Biological Data. 210-221 - Sen Zhang, Jason Tsong-Li Wang:
Mining Frequent Agreement Subtrees in Phylogenetic Databases. 222-233
Clustering
- Zhijie Chen, Weizhen Chen, Qile Chen, Mian-Yun Chen:
Trend Relational Analysis and Grey-Fuzzy Clustering Method. 234-245 - Martin Ester, Rong Ge, Byron J. Gao, Zengjian Hu, Boaz Ben-Moshe:
Joint Cluster Analysis of Attribute Data and Relationship Data: the Connected k-Center Problem. 246-257 - Muna Al-Razgan, Carlotta Domeniconi:
Weighted Clustering Ensembles. 258-269 - Jerry Scripps, Pang-Ning Tan:
Clustering in the Presence of Bridge-Nodes. 270-281
Pattern Mining
- Hongyan Liu, Jiawei Han, Dong Xin, Zheng Shao:
Mining Interesting Patterns from Very High Dimensional Data: A Top-Down Row Enumeration Approach. 282-293 - Jianwei Li, Alok N. Choudhary, Nan Jiang, Wei-keng Liao:
Mining Frequent Patterns by Differential Refinement of Clustered Bitmaps. 294-305 - Jin Soung Yoo, Shashi Shekhar, Sangho Kim, Mete Celik:
Discovery of Co-evoluting Spatial Co-located Event Sets. 306-315 - Evimaria Terzi, Panayiotis Tsaparas:
Efficient Algorithms for Sequence Segmentation. 316-327
Temporal Data and Random Walks
- Feng Cao, Martin Ester, Weining Qian, Aoying Zhou:
Density-Based Clustering over an Evolving Data Stream with Noise. 328-339 - Yunpeng Xu, Xing Yi, Changshui Zhang:
A Random Walks Method for Text Classification. 340-347 - Fosca Giannotti, Mirco Nanni, Dino Pedreschi:
Efficient Mining of Temporally Annotated Sequences. 348-359
Dimension Reduction and Coupling
- Charu C. Aggarwal:
A Framework for Local Supervised Dimensionality Reduction of High Dimensional Data. 360-371 - Ella Bingham, Aristides Gionis, Niina Haiminen, Heli Hiisilä, Heikki Mannila, Evimaria Terzi:
Segmentation and dimensionality reduction. 372-383 - Juan K. Lin:
Probabilistic Multi-State Split-Merge Algorithm for Coupling Parameter Estimates. 384-394
Item Sets
- Arno Siebes, Jilles Vreeken, Matthijs van Leeuwen:
Item Sets that Compress. 395-406 - Jinze Liu, Susan Paulsen, Xing Sun, Wei Wang, Andrew B. Nobel, Jan F. Prins:
Mining Approximate Frequent Itemsets In the Presence of Noise: Algorithm and Analysis. 407-418 - Claudio Lucchese, Salvatore Orlando, Raffaele Perego:
Mining frequent closed itemsets out-of-core. 419-429
Collaborative Mining
- Ran Wolff, Kanishka Bhaduri, Hillol Kargupta:
Local L2-Thresholding Based Data Mining in Peer-to-Peer Systems. 430-441 - Tak-Lam Wong, Wai Lam, Shing-Kit Chan:
Collaborative Information Extraction and Mining from Multiple Web Documents. 442-452 - Khaled M. Hammouda, Mohamed S. Kamel:
Collaborative Document Clustering. 453-463 - Byron J. Gao, Martin Ester:
Cluster Description Formats, Problems and Algorithms. 464-468 - Guimei Liu, Jinyan Li, Limsoon Wong, Wynne Hsu:
Positive Borders or Negative Borders: How to Make Lossless Generator Based Representations Concise. 469-473 - Max Welling, Kenichi Kurihara:
Bayesian K-Means as a "Maximization-Expectation" Algorithm. 474-478 - Charu C. Aggarwal, Philip S. Yu:
A Framework for Clustering Massive Text and Categorical Data Streams. 479-483 - Sei-Hyung Lee, Karen M. Daniels:
Cone Cluster Labeling for Support Vector Clustering. 484-488 - Jing Gao, Pang-Ning Tan, Haibin Cheng:
Semi-Supervised Clustering with Partial Background Information. 489-493 - Geetha Jagannathan, Krishnan Pillaipakkamnatt, Rebecca N. Wright:
A New Privacy-Preserving Distributed k-Clustering Algorithm. 494-498 - Pedro Pereira Rodrigues, João Gama, João Pedro Pedroso:
ODAC: Hierarchical Clustering of Time Series Data Streams. 499-503 - Keke Chen, Ling Liu:
Detecting the Change of Clustering Structure in Categorical Data Streams. 504-508 - Matthew Eric Otey, Srinivasan Parthasarathy, Donald C. Trost:
Dissimilarity Measures for Detecting Hepatotoxicity in Clinical Trial Data. 509-513 - Sreangsu Acharyya:
Transductive De-Noising and Dimensionality Reduction using Total Bregman Regression. 514-518 - Yu Fujimoto, Noboru Murata:
Robust Estimation for Mixture of Probability Tables based on beta-likelihood. 519-523 - Vikas C. Raykar, Ramani Duraiswami:
Fast optimal bandwidth selection for kernel density estimation. 524-528 - Hisashi Kashima:
Risk-Sensitive Learning via Expected Shortfall Minimization. 529-533 - Dongwei Cao, Daniel Boley:
On Approximate Solutions to Support Vector Machines. 534-538 - Eugene Agichtein:
Confidence Estimation Methods for Partially Supervised Information Extraction. 539-543 - Jacek P. Kukluk, Lawrence B. Holder, Diane J. Cook:
Inference of Node Replacement Recursive Graph Grammars. 544-548 - Sheng Zhang, Weihong Wang, James Ford, Fillia Makedon:
Learning from Incomplete Ratings Using Non-negative Matrix Factorization. 549-553 - Yi Fang, Hyun-Woo Cho, Myong Kee Jeong:
Health monitoring of a shaft transmission system via hybrid models of PCR and PLS. 554-558 - Xiaodan Song, Ching-Yung Lin, Belle L. Tseng, Ming-Ting Sun:
Modeling Evolutionary Behaviors for Community-based Dynamic Recommendation. 559-563 - Binyamin Rosenfeld, Ronen Feldman, Moshe Fresko:
A Systematic Cross-Comparison of Sequence Classifiers. 564-568 - Saharon Rosset, Richard D. Lawrence:
Data-Enhanced Predictive Modeling for Sales Targeting. 569-573 - Abraham Bagherjeiran, Chandrika Kamath:
Graph-based Methods for Orbit Classification. 574-578 - Olfa Nasraoui, Suchandra Goswami:
Mining and Validating Localized Frequent Itemsets with Dynamic Tolerance. 579-583 - Saikat Mukherjee, Chang Zhao, I. V. Ramakrishnan:
Profiling Protein Families from Partially Aligned Sequences. 584-588 - Xin Chen, Yi-Fang Wu:
Personalized Knowledge Discovery: Mining Novel Association Rules from Text. 589-593 - Jing Gao, Haibin Cheng, Pang-Ning Tan:
A Novel Framework for Incorporating Labeled Examples into Anomaly Detection. 594-598 - Anthony J. Bonner, Han Liu:
Towards the Prediction of Protein Abundance from Tandem Mass Spectrometry Data. 599-603 - Mehmet M. Dalkilic, Wyatt T. Clark, James C. Costello, Predrag Radivojac:
Using Compression to Identify Classes of Inauthentic Texts. 604-608 - Amol Ghoting, Srinivasan Parthasarathy, Matthew Eric Otey:
Fast Mining of Distance-Based Outliers in High Dimensional Datasets. 609-613 - Yufeng Kou, Chang-Tien Lu, Dechang Chen:
Spatial Weighted Outlier Detection. 614-618 - Olfa Nasraoui, Carlos Rojas:
Robust Clustering for Tracking Noisy Evolving Data Streams. 619-623 - Unil Yun, John J. Leggett:
WIP: mining Weighted Interesting Patterns with a strong weight and/or support affinity. 624-628 - Mark Cheng-Enn Hsieh, Yi-Hung Wu, Arbee L. P. Chen:
Discovering Frequent Tree Patterns over Data Streams. 629-633 - Yan Huang, Liqin Zhang, Pusheng Zhang:
Finding Sequential Patterns from a Massive Number of Spatio-Temporal Events. 634-638 - Roger Ming Hieng Ting, James Bailey:
Mining Minimal Contrast Subgraph Patterns. 639-643
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