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Workshops of the International Conference on Advanced Information Networking and Applications

WAINA 2019: Web, Artificial Intelligence and Network Applications pp 305–313Cite as

Evaluation Measures for Extended Association Rules Based on Distributed Representations

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 927))

Abstract

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.

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Notes

  1. 1.

    https://www.nii.ac.jp/dsc/idr/nico/nico.html.

  2. 2.

    http://www.nicovideo.jp/.

  3. 3.

    https://nlp.stanford.edu/projects/glove/.

  4. 4.

    https://archive.ics.uci.edu/ml/datasets/nursery.

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Acknowledgements

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. College of Humanities and Sciences, Nihon University, 3-25-40 Sakurajosui, Tokyo, 156-8550, Japan

    Tomonobu Ozaki

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  1. Tomonobu Ozaki
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Correspondence to Tomonobu Ozaki .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Department of Advanced Sciences, Hosei University, Koganei-Shi, Tokyo, Japan

    Makoto Takizawa

  3. Department of Computer Science, Technical University of Catalonia, Barcelona, Barcelona, Spain

    Fatos Xhafa

  4. Faculty of Business Administration, Rissho University, Tokyo, Japan

    Tomoya Enokido

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Ozaki, T. (2019). Evaluation Measures for Extended Association Rules Based on Distributed Representations. In: Barolli, L., Takizawa, M., Xhafa, F., Enokido, T. (eds) Web, Artificial Intelligence and Network Applications. WAINA 2019. Advances in Intelligent Systems and Computing, vol 927. Springer, Cham. https://doi.org/10.1007/978-3-030-15035-8_29

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