Title

Efficient Mining Of Strongly Correlated Item Pairs

Keywords

Association rule; Correlation; Data mining; Jaccard's coefficients; Transactional database

Abstract

Past attempts to mine transactional databases for strongly correlated item pairs have been beset by difficulties. In an attempt to be efficient, some algorithms produce false positive and false negative results. In an attempt to be accurate and comprehensive, other algorithms sacrifice efficiency. We propose an efficient new algorithm that uses Jaccard's correlation coefficient, which is simply the ratio between the sizes of the intersection and the union of two sets, to generate a set of strongly correlated item pairs that is both accurate and comprehensive. The pruning of candidate item pairs based on an upper bound facilitates efficiency. Furthermore, there is no possibility of false positives or false negatives. Testing of our algorithm on datasets of various sizes shows its effectiveness in real-world application.

Publication Date

8-23-2006

Publication Title

Proceedings of SPIE - The International Society for Optical Engineering

Volume

6241

Number of Pages

-

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1117/12.664567

Socpus ID

33747367772 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/33747367772

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