JOURNAL ARTICLE

A genetic network programming based method to mine generalized association rules with ontology

Abstract

In this paper, we propose a Genetic Network Programming based method to mine generalized association rules with ontology. We first introduce ontology to facilitate building the multi concept layers and propose Dynamic Threshold Approach (DTA) to equalize the different layers. We make use of an evolutionary computation method Genetic Network Programming (GNP) to mine the rules. Two kinds of fitness functions each with four kinds of policies and a new genetic operator are developed to speed up searching the rule space.

Keywords:
Genetic programming Association rule learning Computer science Ontology Genetic network Operator (biology) Genetic algorithm Computation Genetic representation Association (psychology) Evolutionary computation Data mining Dynamic programming Artificial intelligence Symbolic regression Theoretical computer science Machine learning Algorithm

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FWCI (Field Weighted Citation Impact)
12
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0.11
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Citation History

Topics

Semantic Web and Ontologies
Physical Sciences →  Computer Science →  Artificial Intelligence
Data Mining Algorithms and Applications
Physical Sciences →  Computer Science →  Information Systems
Advanced Database Systems and Queries
Physical Sciences →  Computer Science →  Computer Networks and Communications
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