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題名 Improving the Effectiveness of Experiential Decisions by Recommendation Systems
作者 林靖;許建隆;李有仁
Lin, Arthur J.;Hsu, Chien-Lung;Li, Eldon Y.
貢獻者 資管系
關鍵詞 Recommendation system;Experiential decision;Multilayer perception model;Neural network system;Collaborative filtering system
日期 2014.08
上傳時間 12-Aug-2014 15:46:21 (UTC+8)
摘要 Providing experience-oriented offerings through e-commerce is an issue increasing critical in the growing commoditization of e-commercial services. The high accuracy of predictions rendered by Recommendation System (RS) technologies has strengthened the opportunities for experience-oriented offerings, making RS application an effective way of assisting consumers in online decision-making. This study proposes a RS for movie lovers using neural networks in collaborative filtering systems for consumers’ experiential decisions. The experimental results reveal that it not only improves the accuracy of predicting movie ratings but also increases data transfer rates and provides richer user experiences.
關聯 Expert Systems with Applications, 41(10), 4904-4914
資料來源 http://dx.doi.org/10.1016/j.eswa.2014.01.035
資料類型 article
dc.contributor 資管系en_US
dc.creator (作者) 林靖;許建隆;李有仁zh_TW
dc.creator (作者) Lin, Arthur J.;Hsu, Chien-Lung;Li, Eldon Y.en_US
dc.date (日期) 2014.08en_US
dc.date.accessioned 12-Aug-2014 15:46:21 (UTC+8)-
dc.date.available 12-Aug-2014 15:46:21 (UTC+8)-
dc.date.issued (上傳時間) 12-Aug-2014 15:46:21 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/68621-
dc.description.abstract (摘要) Providing experience-oriented offerings through e-commerce is an issue increasing critical in the growing commoditization of e-commercial services. The high accuracy of predictions rendered by Recommendation System (RS) technologies has strengthened the opportunities for experience-oriented offerings, making RS application an effective way of assisting consumers in online decision-making. This study proposes a RS for movie lovers using neural networks in collaborative filtering systems for consumers’ experiential decisions. The experimental results reveal that it not only improves the accuracy of predicting movie ratings but also increases data transfer rates and provides richer user experiences.en_US
dc.format.extent 958800 bytes-
dc.format.mimetype application/pdf-
dc.language.iso en_US-
dc.relation (關聯) Expert Systems with Applications, 41(10), 4904-4914en_US
dc.source.uri (資料來源) http://dx.doi.org/10.1016/j.eswa.2014.01.035en_US
dc.subject (關鍵詞) Recommendation system;Experiential decision;Multilayer perception model;Neural network system;Collaborative filtering systemen_US
dc.title (題名) Improving the Effectiveness of Experiential Decisions by Recommendation Systemsen_US
dc.type (資料類型) articleen