Proceedings of the Sixth SIAM International Conference on Data Mining

Front Cover
Joydeep Ghosh
SIAM, 2006 M04 1 - 658 pages
The Sixth SIAM International Conference on Data Mining continues the tradition of presenting approaches, tools, and systems for data mining in fields such as science, engineering, industrial processes, healthcare, and medicine. The datasets in these fields are large, complex, and often noisy. Extracting knowledge requires the use of sophisticated, high-performance, and principled analysis techniques and algorithms, based on sound statistical foundations. These techniques in turn require powerful visualization technologies; implementations that must be carefully tuned for performance; software systems that are usable by scientists, engineers, and physicians as well as researchers; and infrastructures that support them.
 

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Contents

CPM A CovarioncePreserving Projection Method
24
A Lotent Dirichlet Model for Unsupervised Entity Resolution
47
Nome Reference Resolution in Organizational Emdi Archives
70
Mining for Outliers in Sequentiol Dotoboses
94
A Doto Mining Approach
118
KMedns Clustering over d Lorge Dynomic Network
153
Contents
154
Exploring Prototypes for Classification
176
Collaborative Information Extraction and Mining from Multiple Web Documents
442
Cluster Description Formots Problems ond Algorithms
464
Boyesian KMedns ds d MaximizationExpectotion Algorithm
474
Cone Cluster Lobeling for Support Vector Clustering
484
A New PrivacyPreserving Distributed kClustering Algorithm
494
Dissimilarity Medsures for Defecting Hepatotoxicity in Clinical Triol Data
509
Robust Estimation for Mixture of Probability Tobles Bosed on 3likelihood
519
RiskSensitive Learning vid Expected Shortfoll Minimization
529

A Semontic Approach for Mining Hidden Links from Complementory ond Noninteractive
200
Mining Frequent Agreement Subtrees in Phylogenetic Databases
222
Trend Relotional Andlysis ond GreyFuzzy Clustering Method
234
Weighted Clustering Ensembles
258
A TopDown Row Enumerotion
282
Discovery of Coevolving Spotiol Event Sets
306
DensityBased Clustering over on Evolving Doto Stredm with Noise
328
Efficient Mining of Temporally Annotated Sequences
348
Segmentation ond Dimensionality Reduction
372
Item Sets Thot Compress
395
Mining Frequent Closed itemsets Out of Core
419
Confidence Estimotion Methods for Portiolly Supervised Relotion Extraction
539
Leorning from Incomplete Rotings Using Nonnegotive Motrix Foctorizotion
549
Modeling Evolutionary Behaviors for CommunityBased Dynamic Recommendation
559
DotoEnhanced Predictive Modeling for Sales Torgeting
569
Mining dnd Volidating Locolized Frequent Itemsets with Dynamic Tolerance
579
Mining Novel Associotion Rules from Text
589
Using Compression to identify Classes of Induthentic Texts
604
Robust Clustering for Tracking Noisy Evolving Doto Streams
619
Finding Sequentiol Potterns from Mossive Number of Spotiotemporal Events
634
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