News Recommendation in Forum-Based Social Media

Authors

  • Jia Wang Southwestern University of Finance and Economics
  • Qing Li Southwestern University of Finance and Economics
  • Yuanzhu Chen Memorial University of Newfoundland, Canada
  • Jiafen Liu Southwestern University of Finance and Economics
  • Chen Zhang
  • Zhangxi Lin Texas Tech University

DOI:

https://doi.org/10.1609/aaai.v24i1.7502

Keywords:

news recommendation, recommender, user comments, content-based filtering

Abstract

Self-publication of news on Web sites is becoming a common application platform to enable more engaging interaction among users. Discussion in the form of comments following news postings can be effectively facilitated if the service provider can recommend articles based on not only the original news itself but also the thread of changing comments. This turns the traditional news recommendation to a "discussion moderator" that can intelligently assist online forums. In this work, we present a framework to implement such adaptive news recommendation. In addition, to alleviate the problem of recommending essentially identical articles, the relationship (duplication, generalization or specialization) between suggested news articles and the original posting is investigated. Experiments indicate that our proposed solutions provide an enhanced news recommendation service in forum-based social media.

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Published

2010-07-05

How to Cite

Wang, J., Li, Q., Chen, Y., Liu, J., Zhang, C., & Lin, Z. (2010). News Recommendation in Forum-Based Social Media. Proceedings of the AAAI Conference on Artificial Intelligence, 24(1), 1449-1454. https://doi.org/10.1609/aaai.v24i1.7502

Issue

Vol. 24 No. 1 (2010): Twenty-Fourth AAAI Conference on Artificial Intelligence

Section

AAAI Technical Track: AI and the Web