Data mining using grammar based genetic programming and applications

Man Leung WONG, Kwong Sak LEUNG

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Abstract

Data mining involves the non-trivial extraction of implicit, previously unknown, and potentially useful information from databases. Genetic Programming (GP) and Inductive Logic Programming (ILP) are two of the approaches for data mining. This book first sets the necessary backgrounds for the reader, including an overview of data mining, evolutionary algorithms and inductive logic programming. It then describes a framework, called GGP (Generic Genetic Programming), that integrates GP and ILP based on a formalism of logic grammars. The formalism is powerful enough to represent context- sensitive information and domain-dependent knowledge. This knowledge can be used to accelerate the learning speed and/or improve the quality of the knowledge induced.
Original languageEnglish
Place of PublicationBoston
PublisherKluwer Academic
ISBN (Print)9780792377467, 9781475784213
DOIs
Publication statusPublished - 2002

Publication series

NameGenetic Programming
PublisherSpringer
Volume3
ISSN (Print)1566-7863

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    WONG, M. L., & LEUNG, K. S. (2002). Data mining using grammar based genetic programming and applications. (Genetic Programming; Vol. 3). Kluwer Academic. https://doi.org/10.1007/b116131