Improved apriori algorithm based on selection criterion

Association rule mining is used to uncover closely related item sets in transactions for deciding business policies. Apriori algorithm is widely adopted is association rule mining for generating closely related item sets. Traditional apriori algorithm is space and time consuming since it requires re...

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Bibliographic Details
Published in2012 IEEE International Conference on Computational Intelligence and Computing Research pp. 1 - 4
Main Authors Vaithiyanathan, V., Rajeswari, K., Phalnikar, R., Tonge, S.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2012
Subjects
Apriori
Association rule mining
Improved Apriori
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ISBN1467313424
9781467313421
DOI10.1109/ICCIC.2012.6510229

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Summary:Association rule mining is used to uncover closely related item sets in transactions for deciding business policies. Apriori algorithm is widely adopted is association rule mining for generating closely related item sets. Traditional apriori algorithm is space and time consuming since it requires repeated scanning of whole transaction database. In this paper we propose improved apriori algorithm based on compressed transaction database. Transaction database is compressed based on the consequence of interest.
ISBN:1467313424
9781467313421
DOI:10.1109/ICCIC.2012.6510229