کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
394000 | 665714 | 2010 | 11 صفحه PDF | دانلود رایگان |
News recommendation and user interaction are important features in many Web-based news services. The former helps users identify the most relevant news for further information. The latter enables collaborated information sharing among users with their comments following news postings. This research is intended to marry these two features together for an adaptive recommender system that utilizes reader comments to refine the recommendation of news in accordance with the evolving topic. This then turns the traditional “push-data” type of news recommendation to “discussion” moderator that can intelligently assist online forums. In addition, to alleviate the problem of recommending essentially identical articles, the relationship (duplicate, generalization, or specialization) between recommended news articles and the original posting is investigated. Our experiments indicate that our proposed solutions provide an improved news recommendation service in forum-based social media.
Journal: Information Sciences - Volume 180, Issue 24, 15 December 2010, Pages 4929–4939