Association rule mining using a multi-objective grammar-based ant programming algorithm

Author

Olmo, Juan Luis ; Luna, José María ; Romero, José Raúl ; Ventura, Sebastián

Author_Institution

Dept. of Comput. Sci. & Numerical Anal., Univ. of Cordoba, Cordoba, Spain

fYear

2011

fDate

22-24 Nov. 2011

Firstpage

971

Lastpage

977

Abstract

This paper presents a method for extracting association rules by means of a multi-objective grammar guided ant programming algorithm. Solution construction is guided by a context-free grammar specifically suited for association rule mining, which defines the search space of all possible expressions or programs. Evaluation of individuals is considered from a Pareto-based point of view, measuring support and confidence of rules mined, and assigning them a ranking fitness. The proposed algorithm is verified over 10 varied data sets and compared to other association rule mining algorithms from several paradigms such as exhaustive search, genetic algorithms and genetic programming, showing that ant programming is a good technique at addressing the association task of data mining as well.

Keywords

ant colony optimisation; context-free grammars; data mining; information retrieval; ant colony optimization; ant programming; association rule mining; context-free grammar; data extraction; multi-objective grammar; search space; Algorithm design and analysis; Association rules; Grammar; Machine learning algorithms; Measurement; Software algorithms; Association rule mining (ARM); ant colony optimization (ACO); ant programming (AP); data mining (DM);

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems Design and Applications (ISDA), 2011 11th International Conference on

Conference_Location

Cordoba

ISSN

2164-7143

Print_ISBN

978-1-4577-1676-8

Type

conf

DOI

10.1109/ISDA.2011.6121784

Filename

6121784