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

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

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    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.

    Original languageEnglish
    Title of host publicationProceedings - 2017 IEEE 10th International Conference on Service-Oriented Computing and Applications, SOCA 2017
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages211-216
    Number of pages6
    Volume2017-January
    ISBN (Electronic)9781538613269
    DOIs
    Publication statusPublished - 2017 Dec 28
    Event10th IEEE International Conference on Service-Oriented Computing and Applications, SOCA 2017 - Kanazawa, Japan
    Duration: 2017 Nov 222017 Nov 25

    Other

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

    Fingerprint

    Electronic commerce
    Recommender systems
    Semantics
    Feedback
    Rating
    Social networks

    Keywords

    • e-commerce
    • recommender system
    • social network
    • trust-aware

    ASJC Scopus subject areas

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

    Cite this

    Liang, W., Zhou, X., Huang, S., Hu, C., & Jin, Q. (2017). Trust-Aware Recommendation for E-Commerce Associated with Social Networks. In Proceedings - 2017 IEEE 10th International Conference on Service-Oriented Computing and Applications, SOCA 2017 (Vol. 2017-January, pp. 211-216). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SOCA.2017.36

    Trust-Aware Recommendation for E-Commerce Associated with Social Networks. / Liang, Wei; Zhou, Xiaokang; Huang, Suzhen; Hu, Chunhua; Jin, Qun.

    Proceedings - 2017 IEEE 10th International Conference on Service-Oriented Computing and Applications, SOCA 2017. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. p. 211-216.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Liang, W, Zhou, X, Huang, S, Hu, C & Jin, Q 2017, Trust-Aware Recommendation for E-Commerce Associated with Social Networks. in Proceedings - 2017 IEEE 10th International Conference on Service-Oriented Computing and Applications, SOCA 2017. vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 211-216, 10th IEEE International Conference on Service-Oriented Computing and Applications, SOCA 2017, Kanazawa, Japan, 17/11/22. https://doi.org/10.1109/SOCA.2017.36
    Liang W, Zhou X, Huang S, Hu C, Jin Q. Trust-Aware Recommendation for E-Commerce Associated with Social Networks. In Proceedings - 2017 IEEE 10th International Conference on Service-Oriented Computing and Applications, SOCA 2017. Vol. 2017-January. Institute of Electrical and Electronics Engineers Inc. 2017. p. 211-216 https://doi.org/10.1109/SOCA.2017.36
    Liang, Wei ; Zhou, Xiaokang ; Huang, Suzhen ; Hu, Chunhua ; Jin, Qun. / Trust-Aware Recommendation for E-Commerce Associated with Social Networks. Proceedings - 2017 IEEE 10th International Conference on Service-Oriented Computing and Applications, SOCA 2017. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. pp. 211-216
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    abstract = "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.",
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