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Published in:
2018 | OriginalPaper | Chapter
Implementation of Academic News Recommendation System Based on User Profile and Message Semantics
Authors : Weiling Li, Yong Tang, Guohua Chen, Danyang Xiao, Chengzhe Yuan
Published in: Computational Intelligence and Intelligent Systems
Publisher: Springer Singapore
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Abstract
The development of academic social network has changed the way researchers make access to academic news. In this paper, we propose a news recommendation system to provide user personalized recommendation based on their profile. Our system presents the generation of user profile: (1) extracts the user tag through TextRank; (2) incorporates the timeliness of the news and generates the user profile according to the users’ behavior; (3) combines the semantic space vector of news, calculate the similarity of the above to make news recommendations. Finally, the experiment is carried out on the academic social network platform - scholat.com. The experimental results show that the news recommendation system can update the user profile in real time, and this recommendation achieves the due goal.