| Inductive Databases and Constraint-Based Data Mining 2010 Edition Contributor(s): Dzeroski, Saso (Editor), Goethals, Bart (Editor), Panov, Panče (Editor) |
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ISBN: 1489982175 ISBN-13: 9781489982179 Publisher: Springer OUR PRICE: $104.49 Product Type: Paperback - Other Formats Published: November 2014 |
| Additional Information |
| BISAC Categories: - Computers | Databases - Data Mining - Computers | Intelligence (ai) & Semantics |
| Dewey: 006.312 |
| Physical Information: 0.96" H x 6.14" W x 9.21" (1.46 lbs) 456 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: 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. |
