Advances in Knowledge Discovery and Management

✍ Scribed by Matthias Studer, Gilbert Ritschard, Alexis Gabadinho, Nicolas S. Müller (auth.), Fabrice Guillet, Gilbert Ritschard, Djamel Abdelkader Zighed, Henri Briand (eds.)

Publisher: Springer-Verlag Berlin Heidelberg
Year: 2010
Tongue: English
Leaves: 339
Series: Studies in Computational Intelligence 292
Edition: 1
Category: Library

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✦ Synopsis

During the last decade, the French-speaking scientific community developed a very strong research activity in the field of Knowledge Discovery and Management (KDM or EGC for “Extraction et Gestion des Connaissances” in French), which is concerned with, among others, Data Mining, Knowledge Discovery, Business Intelligence, Knowledge Engineering and SemanticWeb. The recent and novel research contributions collected in this book are extended and reworked versions of a selection of the best papers that were originally presented in French at the EGC 2009 Conference held in Strasbourg, France on January 2009. The volume is organized in four parts. Part I includes five papers concerned by various aspects of supervised learning or information retrieval. Part II presents five papers concerned with unsupervised learning issues. Part III includes two papers on data streaming and two on security while in Part IV the last four papers are concerned with ontologies and semantic.

✦ Table of Contents

Front Matter....Pages -
Front Matter....Pages 1-1
Discrepancy Analysis of Complex Objects Using Dissimilarities....Pages 3-19
A Bayes Evaluation Criterion for Decision Trees....Pages 21-38
Classifying Very-High-Dimensional Data with Random Forests of Oblique Decision Trees....Pages 39-55
Intensive Use of Correspondence Analysis for Large Scale Content-Based Image Retrieval....Pages 57-76
Toward a Better Integration of Spatial Relations in Learning with Graphical Models....Pages 77-94
Front Matter....Pages 95-95
Multigranular Manipulations for OLAP Querying....Pages 97-112
A New Approach for Unsupervised Classification in Image Segmentation....Pages 113-131
Cluster-Dependent Feature Selection through a Weighted Learning Paradigm....Pages 133-147
Two Variants of the OKM for Overlapping Clustering....Pages 149-166
A Stable Decomposition Algorithm for Dynamic Social Network Analysis....Pages 167-178
Front Matter....Pages 179-179
An Hybrid Data Stream Summarizing Approach by Sampling and Clustering....Pages 181-200
SPAMS: A Novel Incremental Approach for Sequential Pattern Mining in Data Streams....Pages 201-216
Mining Common Outliers for Intrusion Detection....Pages 217-234
Intrusion Detections in Collaborative Organizations by Preserving Privacy....Pages 235-247
Front Matter....Pages 249-249
Alignment-Based Partitioning of Large-Scale Ontologies....Pages 251-269
Learning Ontologies with Deep Class Hierarchies by Mining the Content of Relational Databases....Pages 271-286
Semantic Analysis for the Geospatial Semantic Web....Pages 287-306
Statistically Valid Links and Anti-links BetweenWords and Between Documents: Applying TourneBool Randomization Test to a Reuters Collection....Pages 307-324
Back Matter....Pages -

✦ Subjects

Computational Intelligence; Artificial Intelligence (incl. Robotics)

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