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Search Your Interests Everywhere!: Wikipedia-Based Keyphrase Extraction from Web Browsing History

机译:在任何地方搜索您的兴趣!:基于维基百科的基于Web浏览历史的关键词提取

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This paper proposes a method that can extract user interests from the user's Web browsing history. Our method allows easy access to multiple content domains such as blogs, movies, QA sites, etc. since the user does not need to input a separate search query in each domain/site.To extract user interests, the method first extracts candidate keyphrases from the user's web browsed documents. Second, important keyphrases obtained from a link structure analysis of Wikipedia content is extracted from the main contents of web documents. This technique is based on the idea that important keyphrases in Wikipedia are important keyphrases in the real world. Finally, keyphrases contained in the documents important to the user are set in order as user interests. An experiment shows that our method offers improvements over a conventional method and can recommend interests attractive to the user.
机译:本文提出了一种可以从用户的Web浏览历史中提取用户兴趣的方法。我们的方法允许轻松访问多个内容域,例如博客,电影,QA站点等。由于用户无需在每个域/站点中输入单独的搜索查询。要提取用户兴趣,该方法首先提取来自候选关键次数用户的Web浏览文档。其次,从Wikipedia含量的链路结构分析中获得的重要关键酶从Web文档的主要内容中提取。这种技术基于Wikipedia中的重要关键术语是现实世界中的重要关键效果。最后,将包含在用户的文件中包含的密钥阵列作为用户兴趣来设置。实验表明,我们的方法提供了通过传统方法的改进,并推荐对用户有吸引力的兴趣。

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