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Association Rule Mining of Personal Hobbies in Social Networks

Association Rule Mining of Personal Hobbies in Social Networks

Xiaoqing Yu, Shimin Miao, Huanhuan Liu, Jenq-Neng Hwang, Wanggen Wan, Jing Lu
Copyright: © 2017 |Volume: 14 |Issue: 1 |Pages: 16
ISSN: 1545-7362|EISSN: 1546-5004|EISBN13: 9781522511113|DOI: 10.4018/IJWSR.2017010102
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MLA

Yu, Xiaoqing, et al. "Association Rule Mining of Personal Hobbies in Social Networks." IJWSR vol.14, no.1 2017: pp.13-28. http://doi.org/10.4018/IJWSR.2017010102

APA

Yu, X., Miao, S., Liu, H., Hwang, J., Wan, W., & Lu, J. (2017). Association Rule Mining of Personal Hobbies in Social Networks. International Journal of Web Services Research (IJWSR), 14(1), 13-28. http://doi.org/10.4018/IJWSR.2017010102

Chicago

Yu, Xiaoqing, et al. "Association Rule Mining of Personal Hobbies in Social Networks," International Journal of Web Services Research (IJWSR) 14, no.1: 13-28. http://doi.org/10.4018/IJWSR.2017010102

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Abstract

In this paper, the authors propose an effective scheme for association rule mining of personal hobbies in social networks. By introducing the connection and clipping techniques, the authors are able to ignore unrelated items in the process of finding frequent itemsets, resulting in more accurate candidate itemsets. More specifically, set operations, which are used in the process of combining frequent itemsets, can dramatically reduce the number of databases visited. Furthermore, to explore more practical rules, interestingness level is also introduced to eliminate rules that few people are interested in. The authors' proposed association rule mapping is shown to be able to provide new insights for supporting personalized services and virtual marketing.

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