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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/111674


    Title: SNS opinion-based recommendation for eTourism: A Taipei restaurant example
    Authors: 趙逢毅
    Chao, August F.Y.
    Lai, Cheng-Yu
    Contributors: 資管系
    Keywords: Big data;Decision support systems;Internet;Product design;Semantics;Social networking (online);Websites;eTourism;Latent Semantic Analysis;Recommendation;Social networking sites;User-generated content;Case based reasoning
    Date: 2015-09
    Issue Date: 2017-08-08 16:49:02 (UTC+8)
    Abstract: By the use of Internet technology in the travel and tourism industry, tourists are considered to play more significant role in the process of planning and designing tourism-related products and services. The amount of information that can acquire from Internet may far exceed one can handle, and makes the decision considerations in the travel planning process fairly complicated. Yu [3] proposed an integrated functional framework and design process for providing web-based personalized and community decision support services, and argue to extract user experiences by using case-based reasoning. However, to construct patterns from case-based reasoning among gigantic amount of user-generated content is a heavy-loading task. In this study, we adopted latent semantic analysis (LSA) [8, 9], which is constructed language pattern and discover semantic relationship between topics in big data scenario, to recommend restaurant according to desiring for similar experience. Both academic and practical implications of proposed approach are also discussed. © Springer-Verlag Berlin Heidelberg 2015.
    Relation: Communications in Computer and Information Science, 540, 393-403
    2nd International Conference on Multidisciplinary Social Networks Research, MISNC 2015; Matsuyama; Japan; 1 September 2015 到 3 September 2015; 代碼 140409
    Data Type: conference
    DOI link: http://dx.doi.org/10.1007/978-3-662-48319-0_32
    DOI: 10.1007/978-3-662-48319-0_32
    Appears in Collections:[Department of MIS] Proceedings

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