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Temporal Fuzzy Association Rule Mining with 2-tuple Linguistic Representation
Matthews, Stephen G.; Gongora, Mario A.; Hopgood, Adrian et al.
2012In 2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2012)
Peer reviewed
 

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Abstract :
[en] This paper reports on an approach that contributes towards the problem of discovering fuzzy association rules that exhibit a temporal pattern. The novel application of the 2-tuple linguistic representation identifies fuzzy association rules in a temporal context, whilst maintaining the interpretability of linguistic terms. Iterative Rule Learning (IRL) with a Genetic Algorithm (GA) simultaneously induces rules and tunes the membership functions. The discovered rules were compared with those from a traditional method of discovering fuzzy association rules and results demonstrate how the traditional method can loose information because rules occur at the intersection of membership function boundaries. New information can be mined from the proposed approach by improving upon rules discovered with the traditional method and by discovering new rules.
Disciplines :
Computer science
Electrical & electronics engineering
Author, co-author :
Matthews, Stephen G.;  De Montfort Univ, Ctr Computat Intelligence, Leicester LE1 9BH, Leics, England.
Gongora, Mario A.;  De Montfort Univ, 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, Ctr Computat Intelligence, Leicester LE1 9BH, Leics, England.
Language :
English
Title :
Temporal Fuzzy Association Rule Mining with 2-tuple Linguistic Representation
Publication date :
2012
Event name :
IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
Event organizer :
IEEE
Event place :
Brisbane, Australia
Event date :
JUN 10-15, 2012
Audience :
International
Main work title :
2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2012)
Publisher :
IEEE
ISBN/EAN :
978-1-4673-1507-4
Peer reviewed :
Peer reviewed
Commentary :
978-1-4673-1506-7
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