Web usage mining with evolutionary extraction of temporal fuzzy association rules

Fuzzy association rules; Temporal association rules; Evolutionary fuzzy system; Genetic algorithm; Data mining; Analytics; Rule discovery; 2-tuple linguistic representation

Abstract :

[en] In Web usage mining, fuzzy association rules that have a temporal property can provide useful knowledge about when associations occur. However, there is a problem with traditional temporal fuzzy association rule mining algorithms. Some rules occur at the intersection of fuzzy sets' boundaries where there is less support (lower membership), so the rules are lost. A genetic algorithm (GA)-based solution is described that uses the flexible nature of the 2-tuple linguistic representation to discover rules that occur at the intersection of fuzzy set boundaries. The GA-based approach is enhanced from previous work by including a graph representation and an improved fitness function. A comparison of the GA-based approach with a traditional approach on real-world Web log data discovered rules that were lost with the traditional approach. The GA-based approach is recommended as complementary to existing algorithms, because it discovers extra rules. (C) 2013 Elsevier B.V. All rights reserved.

Disciplines :

Computer science

Author, co-author :

Matthews, Stephen G.; Univ Bristol, Dept Engn Math, Intelligent Syst Lab, Bristol BS8 1UB, Avon, England.

Gongora, Mario A.; De Montfort Univ, Dept Informat, Ctr Computat Intelligence, Leicester LE1 9BH, Leics, England.

Hopgood, Adrian ; Université de Liège > HEC - Ecole de gestion de l'ULG : Direction générale

Ahmadi, Samad; De Montfort Univ, Dept Informat, Ctr Computat Intelligence, Leicester LE1 9BH, Leics, England.

Language :

English

Title :

Web usage mining with evolutionary extraction of temporal fuzzy association rules

Publication date :

2013

Journal title :

Knowledge-Based Systems

ISSN :

0950-7051

eISSN :

1872-7409

Publisher :

Elsevier Science Bv, Amsterdam, Netherlands

Special issue title :

Volume :

Pages :

66-72

Peer reviewed :

Peer Reviewed verified by ORBi

Available on ORBi :

since 11 February 2016

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