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Item Details
Title: INDUCTIVE DATABASES AND CONSTRAINT-BASED DATA MINING
By: Saso Dzeroski (Editor), Bart Goethals (Editor), Pance Panov (Editor)
Format: Hardback

List price: £119.99


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ISBN 10: 1441977376
ISBN 13: 9781441977373
Publisher: SPRINGER-VERLAG NEW YORK INC.
Pub. date: 2 November, 2010
Edition: 2010 ed.
Pages: 456
Description: This presentation of emergent research topics at the intersection of data mining and database research covers the state of the art in this field as well as examining its applications to problems of practical relevance such as those in bioinformatics.
Synopsis: This book is about inductive databases and constraint-based data mining, emerging research topics lying at the intersection of data mining and database research. The aim of the book as to provide an overview of the state-of- the art in this novel and - citing research area. Of special interest are the recent methods for constraint-based mining of global models for prediction and clustering, the uni?cation of pattern mining approaches through constraint programming, the clari?cation of the re- tionship between mining local patterns and global models, and the proposed in- grative frameworks and approaches for inducive databases. On the application side, applications to practically relevant problems from bioinformatics are presented. Inductive databases (IDBs) represent a database view on data mining and kno- edge discovery. IDBs contain not only data, but also generalizations (patterns and models) valid in the data. In an IDB, ordinary queries can be used to access and - nipulate data, while inductive queries can be used to generate (mine), manipulate, and apply patterns and models. In the IDB framework, patterns and models become "?rst-class citizens" and KDD becomes an extended querying process in which both the data and the patterns/models that hold in the data are queried.
Illustrations: XVII, 456 p.
Publication: US
Imprint: Springer-Verlag New York Inc.
Returns: Returnable
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