Evaluation Measures for Extended Association Rules Based on Distributed Representations

  • Tomonobu OzakiEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 927)


Indirect association rules and association action rules are two notable extensions of traditional association rules. Since these two extended rules consist of a pair of association rules, they share the same essential drawback of association rules: a huge number of rules will be derived if the target database to be mined is dense or the minimum threshold is set low. One practical approach for alleviating this essential drawback is to rank the rules to identify which one to be examined first in a post-processing. In this paper, as a new application of representation learning, we propose evaluation measures for indirect association rules and association action rules, respectively. The proposed measures are assessed preliminary using a dataset on Japanese video-sharing site and that on nursery.



In this paper, the author used the “Nicovideo dataset” provided by National Institute of Informatics. This work was partially supported by JSPS KAKENHI Grant Number 17K00315.


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Authors and Affiliations

  1. 1.College of Humanities and SciencesNihon UniversityTokyoJapan

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