Title: Recommending blog articles based on popular event trend analysis
Authors: Liu, Duen-Ren
Omar, Hani
Liou, Chuen-He
Chi, Huai-Chun
Hsu, Cheng-Ho
資訊管理與財務金融系 註:原資管所+財金所
Department of Information Management and Finance
Keywords: Blogosphere;Popular event-based recommendation;Trend analysis;Google Insights;Content-based filtering;Item-based collaborative filtering
Issue Date: 1-Jun-2015
Abstract: Web 2.0 has become a popular social media on the Internet due to the fast evolution of Internet technologies, as well as increasing resources and users. Among the applications of Web 2.0, blogospheres are a new Internet social media for users to express their preferences and personal feelings. Most of the people tend to receive the newest information and articles related to popular issues. However, with the rapidly increasing number of active writers and viewers, it is hard for people to discover useful information that is beneficial or interesting to them. Accordingly, it is necessary to develop a recommendation approach that takes the emerging or popular events into consideration. In this work, we propose a novel event-based recommendation approach, which combines the event trend analysis and personal preference to recommend blog articles of popular events that suit user interests. We analyze blog articles to identify popular events, and then derive the popularity degrees of events based on blog-based popularity trend analysis and Google Insights-based popularity trend analysis. Our approach derives users\' personalized preferences on target articles of popular events by considering user interests (article-push records) and the predicted popularity degree of the events. Our recommendation methods improve recommendation accuracy by enhancing content-based filtering (CBF) and item-based collaborative filtering (ICF) with the event-based preference analysis. Our experiment result demonstrates that the proposed approach can effectively recommend users\' desired blog articles with respect to event popularity and personal interests. (C) 2015 Elsevier Inc. All rights reserved.
URI: http://dx.doi.org/10.1016/j.ins.2015.02.003
ISSN: 0020-0255
DOI: 10.1016/j.ins.2015.02.003
Volume: 305
Begin Page: 302
End Page: 319
Appears in Collections:Articles