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    Please use this identifier to cite or link to this item: http://ir.cnu.edu.tw/handle/310902800/27550


    標題: Designing a Personalized Guide Recommendation System to Mitigate Information Overload in Museum Learning
    作者: Huang, Yong-Ming
    Liu, Chien-Hung
    Lee, Chun-Yi
    Huang, Yueh-Min
    貢獻者: 應用空間資訊系
    關鍵字: Museum Learning
    Information Overload
    Personalized Guide Recommendation
    Association Rule Mining
    日期: 2012-10
    上傳時間: 2014-03-21 16:13:11 (UTC+8)
    出版者: Ieee Computer Soc
    摘要: Museum learning has received a lot of attention in recent years. Museum learning refers to people's use of museums to acquire knowledge. However, a problem with information overload has caused in engaging in such learning. Information overload signifies that users encounter a mass of information and need to determine whether certain information needs to be retained. In this paper, we proposed a personalized guide recommendation (PGR) system to mitigate this problem. The system used association rule mining to discover guide recommendation rules both from collective visiting behavior and individual visiting behavior, and then the rules were personalized. Using this system, visitors can obtain a PGR and avoid exposure to excessive exhibit information. To investigate user satisfaction with the PGR system, a user satisfaction questionnaire was developed to analyze the user satisfaction in a sample consisting of individuals of different genders and ages. The results showed that both men and women consistently accepted the PGR system and revealed that there were significant differences with regard to attitudes toward the system's service quality among different user ages. It was inferred that one possible reason for this was an effect related to users' prior experience with computers. A summary of the findings suggested that the PGR system generally obtained positive feedback.
    關聯: Educational Technology & Society, v.15 n.4 pp.150-166
    Appears in Collections:[應用空間資訊系(所)] 期刊論文

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