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dc.contributor.authorLiu, Duen-Renen_US
dc.contributor.authorTsai, Pei-Yunen_US
dc.contributor.authorChiu, Po-Huanen_US
dc.date.accessioned2014-12-08T15:11:43Z-
dc.date.available2014-12-08T15:11:43Z-
dc.date.issued2011-05-01en_US
dc.identifier.issn0020-0255en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.ins.2011.01.005en_US
dc.identifier.urihttp://hdl.handle.net/11536/8977-
dc.description.abstractWeblogs have emerged as a new communication and publication medium on the Internet for diffusing the latest useful information. Providing value-added mobile services, such as blog articles, is increasingly important to attract mobile users to mobile commerce, in order to benefit from the proliferation and convenience of using mobile devices to receive information any time and anywhere. However, there are a tremendous number of blog articles, and mobile users generally have difficulty in browsing weblogs owing to the limitations of mobile devices. Accordingly, providing mobile users with blog articles that suit their particular interests is an important issue. Very little research, however, has focused on this issue. In this work, we propose a novel Customized Content Service on a mobile device (m-CCS) to filter and push blog articles to mobile users. The m-CCS includes a novel forecasting approach to predict the latest popular blog topics based on the trend of time-sensitive popularity of weblogs. Mobile users may, however, have different interests regarding the latest popular blog topics. Thus, the m-CCS further analyzes the mobile users' browsing logs to determine their interests, which are then combined with the latest popular blog topics to derive their preferred blog topics and articles. A novel hybrid approach is proposed to recommend blog articles by integrating personalized popularity of topic clusters, item-based collaborative filtering (CF) and attention degree (click times) of blog articles. The experiment result demonstrates that the m-CCS system can effectively recommend mobile users' desired blog articles with respect to both popularity and personal interests. (C) 2011 Elsevier Inc. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectMobile serviceen_US
dc.subjectBlog recommendersen_US
dc.subjectTime-sensitive topicen_US
dc.subjectCollaborative filteringen_US
dc.titlePersonalized recommendation of popular blog articles for mobile applicationsen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.ins.2011.01.005en_US
dc.identifier.journalINFORMATION SCIENCESen_US
dc.citation.volume181en_US
dc.citation.issue9en_US
dc.citation.spage1552en_US
dc.citation.epage1572en_US
dc.contributor.department資訊管理與財務金融系 註:原資管所+財金所zh_TW
dc.contributor.departmentDepartment of Information Management and Financeen_US
dc.identifier.wosnumberWOS:000288774700004-
dc.citation.woscount18-
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