A restaurant recommender system based on user preference and location in mobile environment

Jun Zeng, Feng Li, Haiyang Liu, Junhao Wen, Sachio Hirokawa

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

    19 Citations (Scopus)

    Abstract

    Recommender system is an effective way to help users to obtain the personalized and useful information. However, due to complexity and dynamic, the traditional recommender system cannot work well in mobile environment. In this paper, we propose a restaurant recommender system in mobile environment. This recommender system adopts a user preference model by using the features of user's visited restaurants, and also utilizes the location information of user and restaurants to dynamically generate the recommendation results. Baidu map cloud service is used to implement the proposed recommender system. The result of a case study shows that the proposed restaurant recommender system can effectively utilize user's preference and the location information to recommend the personalized and suitable restaurants for different users.

    Original languageEnglish
    Title of host publicationProceedings - 2016 5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016
    EditorsAyako Hiramatsu, Tokuro Matsuo, Akimitsu Kanzaki, Norihisa Komoda
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages55-60
    Number of pages6
    ISBN (Electronic)9781467389853
    DOIs
    Publication statusPublished - Aug 31 2016
    Event5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016 - Kumamoto, Japan
    Duration: Jul 10 2016Jul 14 2016

    Publication series

    NameProceedings - 2016 5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016

    Other

    Other5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016
    CountryJapan
    CityKumamoto
    Period7/10/167/14/16

    All Science Journal Classification (ASJC) codes

    • Information Systems
    • Computer Networks and Communications
    • Computer Science Applications
    • Computer Vision and Pattern Recognition

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