Inductive Databases and Constraint-Based Data Mining (Paperback, 2010 ed.)

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.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Release date:	November 2014
First published:	2010
Editors:	Saso Dzeroski • Bart Goethals • Pance Panov
Dimensions:	235 x 155 x 24mm (L x W x T)
Format:	Paperback
Pages:	456
Edition:	2010 ed.
ISBN-13:	978-1-4899-8217-9
Categories:	Books > Science & Mathematics > Biology, life sciences > Life sciences: general issues > General Books > Computing & IT > Applications of computing > Databases > Data mining Books > Computing & IT > Applications of computing > Artificial intelligence > General Promotions
LSN:	1-4899-8217-5
Barcode:	9781489982179

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