Trust-Aware Recommendation for E-Commerce Associated with Social Networks

Wei Liang, Xiaokang Zhou, Suzhen Huang, Chunhua Hu, Qun Jin

研究成果: Conference contribution

抄録

In recent years, recommender systems are widely applied in e-commerce system to help users locating their interested information. However, the 'all good reputation' problem brings down the accuracy of recommender systems. In addition, users' social network can benefit the recommendation especially when dealing with cold-start scenarios. In this paper, a novel trust-aware recommendation approach for e-commerce is proposed, which unearths the hint from ordinary rating and trust network by users' instant interactions in e-commerce system. More precisely, a rating revamping algorithm is designed to extract semantic ratings from feedback comments, and further construct fine grained rating score for the next process. Then, the recommendation scheme is studied through analyzing the users' trust network and their own behavior in e-commerce system. Finally, evaluations conducted based on a real dataset 'Douban' to demonstrate the effectiveness of the proposed method.

本文言語English
ホスト出版物のタイトルProceedings - 2017 IEEE 10th International Conference on Service-Oriented Computing and Applications, SOCA 2017
出版社Institute of Electrical and Electronics Engineers Inc.
ページ211-216
ページ数6
ISBN(電子版)9781538613269
DOI
出版ステータスPublished - 2017 12 28
イベント10th IEEE International Conference on Service-Oriented Computing and Applications, SOCA 2017 - Kanazawa, Japan
継続期間: 2017 11 222017 11 25

出版物シリーズ

名前Proceedings - 2017 IEEE 10th International Conference on Service-Oriented Computing and Applications, SOCA 2017
2017-January

Other

Other10th IEEE International Conference on Service-Oriented Computing and Applications, SOCA 2017
CountryJapan
CityKanazawa
Period17/11/2217/11/25

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems and Management

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