2009 International Conference on Business Intelligence and Financial Engineering A Survey of Interestingness Measures for Association Rules Beijing, China July 24-July 26 ISBN: 978-0-7695-3705-4
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/BIFE.2009.110
Association mining can generate large quantity of rules, most of which are not interesting to the user. Interestingness measures are used to find the truly interesting rules. This paper presents a review of the available literature on the various interestingness measures, which generally can be divided into two categories: objective measures based on the statistical strengths or properties of the discovered rules, and subjective measures which are derived from the user’s beliefs or expectations of their particular problem domain. We sum up twelve measure criteria which are concerned by many researchers and evaluate the strengths and weaknesses of the two categories of measures. At last, we pointed out that the combination of objective and subjective measures would be a possible research direction.
Index Terms:
association rules, interestingness measure, objective measure, subjective measure
Citation:
Yuejin Zhang, Lingling Zhang, Guangli Nie, Yong Shi, "A Survey of Interestingness Measures for Association Rules," bife, pp.460-463, 2009 International Conference on Business Intelligence and Financial Engineering, 2009 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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