Information Fusion in Data Mining / Edition 1

by Prof. Vicenç Torra

Overview

Information fusion is becoming a major requirement in data mining and knowledge discovery in databases. This book presents some recent fusion techniques that are currently in use in data mining, as well as data mining applications that use information fusion. Special focus of the book is on information fusion in preprocessing, model building and information extraction with various applications.

Product Details

ISBN-13:	9783642056284
Publisher:	Springer Berlin Heidelberg
Publication date:	12/14/2010
Series:	Studies in Fuzziness and Soft Computing , #123
Edition description:	Softcover reprint of hardcover 1st ed. 2003
Pages:	234
Product dimensions:	6.10(w) x 9.25(h) x 0.02(d)

Table of Contents

Trends in Information fusion in Data Mining.- On some aggregation operators for numerical information.- Choquet integral and Sugeno integral in the Particle Deflection Plane.- Data Mining Using a Probabilistic Weighted Ordered Weighted Average (PWOWA) Operator.- Mining Interesting Patterns in Multiple Data Sources.- Discovery of Temporal Knowledge in Medical Time-Series Databases using Moving Average, Multiscale Matching and Rule Induction.- Record linkage methods for multidatabase data mining.- Modelling data by the Choquet integral.- An Algorithm Based on Alternative Projections for a Fuzzy Measure Identification Problem.- Combining Information Fusion with String Pattern Analysis: A New Method for Predicting Future Purchase Behavior.- Ensemble Learnig by a Fuzzy Classification Systems for Pattern Classification.- Data Mining Using Granular Linguistic Summaries.