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Inductive Databases and Constraint-Based Data Mining

Editors: Dzeroski, Saso, Goethals, Bart, Panov, Panče (Eds.)

  • Provides a broad and unifying perspective on the field of data mining in general and inductive databases in particular
  • Includes discussion of constraint-based mining of predictive models for structured data/outputs, and integration/unification of pattern and model mining at the conceptual level
  • Examines applications to practically relevant problems in bioinformatics
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eBook $139.00
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  • ISBN 978-1-4419-7738-0
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  • Included format: PDF
  • ebooks can be used on all reading devices
  • Download immediately after purchase
Hardcover $179.00
price for USA
  • ISBN 978-1-4419-7737-3
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $179.00
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  • ISBN 978-1-4899-8217-9
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

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.

Table of contents (18 chapters)

  • Inductive Databases and Constraint-based Data Mining: Introduction and Overview

    Džeroski, Sašo

    Pages 3-26

  • Representing Entities in the OntoDM Data Mining Ontology

    Panov, Panče (et al.)

    Pages 27-58

  • A Practical Comparative Study Of Data Mining Query Languages

    Blockeel, Hendrik (et al.)

    Pages 59-77

  • A Theory of Inductive Query Answering

    Raedt, Luc (et al.)

    Pages 79-103

  • Generalizing Itemset Mining in a Constraint Programming Setting

    Besson, Jérémy (et al.)

    Pages 107-126

Buy this book

eBook $139.00
price for USA
  • ISBN 978-1-4419-7738-0
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Download immediately after purchase
Hardcover $179.00
price for USA
  • ISBN 978-1-4419-7737-3
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $179.00
price for USA
  • ISBN 978-1-4899-8217-9
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Inductive Databases and Constraint-Based Data Mining
Editors
  • Saso Dzeroski
  • Bart Goethals
  • Panče Panov
Copyright
2010
Publisher
Springer-Verlag New York
Copyright Holder
Springer Science+Business Media, LLC
eBook ISBN
978-1-4419-7738-0
DOI
10.1007/978-1-4419-7738-0
Hardcover ISBN
978-1-4419-7737-3
Softcover ISBN
978-1-4899-8217-9
Edition Number
1
Number of Pages
XVII, 456
Topics