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저자 Jaekwang Kim, KwangHo Yoon, Jee-Hyong Lee 
논문지 IEICE TRANSACTIONS on Communications 
Vol. E95-B 
No.
pp. 1558-1565 
게재일 2012-05-01 
Clickstreams in users' navigation logs have various data which are related to users' web surfing. Those are visit counts, stay times, product types, etc. When we observe these data, we can divide clickstreams into sub-clickstreams so that the pages in a sub-clickstream share more contexts with each other than with the pages in other sub-clickstreams. In this paper, we propose a method which extracts more informative rules from clickstreams for web page recommendation based on genetic programming and association rules. First, we split clickstreams into sub-clickstreams by contexts for generating more informative rules. In order to split clickstreams in consideration of context, we extract six features from users' navigation logs. A set of split rules is generated by combining those features through genetic programming, and then informative rules for recommendation are extracted with the association rule mining algorithm. Through experiments, we verify that the proposed method is more effective than the other methods in various conditions.

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      An Auto Playlist Generation System with One Seed Song
      2012.03.19
      저자: Sung-Woo Bang, Hye-Wuk Jung, Jaekwang Kim, and Jee-Hyong Lee     논문지: International Journal of Fuzzy Logic and Intelligent Systems     Vol.: 10     No.: 1     pp.: 19-24     게재일: 2010-03-01