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一种基于潜在类别模型的新闻推荐方法 被引量：3

A News Recommending Approach Based on Latent Model
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摘要 设计一种基于潜在类别模型的新闻推荐模型,包含用户、新闻关键词和新闻类别三个外显变量及一个潜在类别变量。将用户、新闻和类别分别归类到相应的潜在类别中,根据用户兴趣偏好预测用户登陆新闻网站后可能访问的新闻项,生成个性化的新闻推荐序列,并通过实验证明了该三元模型的优越性。 We present a news recommending model based on latent model, including three manifest variables, such as user, news items and news categories, and a latent variable, which classifies the manifest variables into corresponding latent categories. It can predict the news items users may read after gaining access to the news website and generate personalized news rankings according to users＆#39; prefer-ences. Experiments show the superiority of the triadic model.
作者 文鹏 蔡瑞 吴黎兵
机构地区 武汉大学信息管理学院 武汉 武汉大学计算机学院 武汉
出处 《情报杂志》 CSSCI 北大核心 2014年第1期161-166,共6页 Journal of Intelligence
基金 国家自然科学基金项目“网格资源提前预留性能优化关键问题的研究”(编号:61070010) 国家自然科学基金项目“面向物联网环境的大规模可扩展网络管理研究”(编号:61272122)
关键词 潜在类别模型 用户偏好 用户模型 新闻推荐 latent model user preference user profile news recommending
分类号 TP311 [自动化与计算机技术—计算机软件与理论]
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参考文献16

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二级参考文献216

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共引文献1024

同被引文献26

  • 1JIANG S, HONG W X. A vertical news recommendation system: CCNS——an example from Chinese campus news reading system[C]//ICCSE 2014: Proceedings of the 2014 9th International Conference on Computer Science & Education. Piscataway, NJ: IEEE, 2014: 1105-1114.
  • 2DAS A S, DATAR M, GARG A, et al. Google news personalization: scalable online collaborative filtering[C]//WWW '07: Proceedings of the 16th International Conference on World Wide Web. New York: ACM, 2007: 271-280.
  • 3GARCIN F, ZHOU K, FALTINGS B, et al. Personalized news recommendation based on collaborative filtering[C]//WI-IAT '12: Proceedings of the 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology. Washington, DC: IEEE Computer Society, 2012, 1: 437-441.
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  • 6ADNAN M N M, CHOWDURY M R, TAZ I, et al. Content based news recommendation system based on fuzzy logic[C]//ICIEV 2014: Proceedings of the 2014 International Conference on Informatics, Electronics & Vision. Washington, DC: IEEE Computer Society, 2014: 1-6.
  • 7LIU J, DOLAN P, PEDERSEN E R. Personalized news recommendation based on click behavior[C]//IUI '10: Proceedings of the 15th International Conference on Intelligent User Interfaces. New York: ACM, 2010: 31-40.
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  • 9LEE W-J, OH K-J, LIM C-G, et al. User profile extraction from Twitter for personalized news recommendation[C]//ICACT 2014: Proceedings of the 2014 16th International Conference on Advanced Communication Technology. Washington, DC: IEEE Computer Society, 2014: 779-783.
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