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User Comments for News Recommendation in Social Media

机译:用户评论社交媒体中的新闻推荐

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摘要

Reading and Commenting online news is becoming a common user behavior in social media. 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 recommend relevant information in the forum-based social media using user comments. When incorporating user comments, we consider structural and semantic information carried by them. Experiments indicate that our proposed solutions provide an effective recommendation service.
机译:阅读和评论在线新闻正在成为社交媒体中一种常见的用户行为。如果服务提供商不仅可以基于原始新闻本身,而且可以基于更改评论的线索来推荐文章,则可以有效地促进新闻发布之后以评论形式进行的讨论。这将传统的新闻推荐变成了“讨论主持人”,可以智能地帮助在线论坛。在这项工作中,我们提供了一个框架,可以使用用户评论在基于论坛的社交媒体中推荐相关信息。在合并用户评论时,我们会考虑它们所携带的结构和语义信息。实验表明,我们提出的解决方案可提供有效的推荐服务。

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