ENGLISH

Data Mining and Knowledge Discovery Approaches Based on Rule Induction Techniques

By Arkadij D. Zakrevskij (auth.) , Evangelos Triantaphyllou , Giovanni Felici (eds.)

Book information

Publisher
Springer US
Year
2006
ISBN
0387342966, 038734294X, 9780387342948
DOI
10.1007/0-387-34296-6
Open Library ID
OL7445589M
Language
english
Format
PDF
Filesize
43 MB (45275944 bytes)
Series
Massive Computing 6
Edition
1
Pages
748\775
Library
mexmat
Time added
2009-07-20 03:45:11
Information Storage and Retrieval; Operations ReseMathematical Programming; Operations Research/Deci

Description

This book will give the reader a perspective into the core theory and practice of data mining and knowledge discovery (DM&KD). Its chapters combine many theoretical foundations for various DM&KD methods, and they present a rich array of examples—many of which are drawn from real-life applications. Most of the theoretical developments discussed are accompanied by an extensive empirical analysis, which should give the reader both a deep theoretical and practical insight into the subjects covered. The book presents the combined research experiences of its 40 authors gathered during a long search in gleaning new knowledge from data. The last page of each chapter has a brief biographical statement of its contributors, who are world-renowned experts. Audience The intended audience for this book includes graduate students studying data mining who have some background in mathematical logic and discrete optimization, as well as researchers and practitioners in the same area.

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