Inductive Databases and Constraint-Based Data Mining

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106,99 

ISBN: 1489982175
ISBN 13: 9781489982179
Herausgeber: Saso Dzeroski/Bart Goethals/Pance Panov
Verlag: Springer Verlag GmbH
Umfang: xvii, 456 S.
Erscheinungsdatum: 13.11.2014
Auflage: 1/2014
Produktform: Kartoniert
Einband: Kartoniert

Provides a broad and unifying perspective on the field of data mining in general and inductive databases in particularIncludes constraint-based mining of predictive models for structured data/outputs, integration/unification of pattern and model mining at the conceptual levelDiscusses applications to practically relevant problems in bioinformaticsIncludes supplementary material: sn.pub/extras

Artikelnummer: 7806997 Kategorie:

Beschreibung

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.

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