Customizing knowledge-based recommender system by tracking analysis of user behavior

Xiaohui Li*, Tomohiro Murata

*この研究の対応する著者

研究成果: Conference contribution

9 被引用数 (Scopus)

抄録

In this paper, we reviewed the major problems in the existing recommender systems and presented a tracking recommender approach based on user's behavior information and two-level property of items. Our proposed approach defined user profile model, knowledge resources model and constructed Formal Concept Analysis (FCA) mapping to guide a personalized recommendation for user. We simulated a prototype recommender system that can make the quality recommendation by tracking user's behavior. The experimental result showed our strategy was more robust against the drawbacks and preponderant than conventional recommender systems.

本文言語English
ホスト出版物のタイトルProceedings - 2010 IEEE 17th International Conference on Industrial Engineering and Engineering Management, IE and EM2010
ページ65-69
ページ数5
DOI
出版ステータスPublished - 2010 12月 31
イベント17th International Conference on Industrial Engineering and Engineering Management, IE and EM2010 - Xiamen, China
継続期間: 2010 10月 292010 10月 31

出版物シリーズ

名前Proceedings - 2010 IEEE 17th International Conference on Industrial Engineering and Engineering Management, IE and EM2010

Conference

Conference17th International Conference on Industrial Engineering and Engineering Management, IE and EM2010
国/地域China
CityXiamen
Period10/10/2910/10/31

ASJC Scopus subject areas

  • 産業および生産工学

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