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Diversifying Microblog Posts

机译:微博帖子多样化

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摘要

Microblogs have become an important source of information, a medium for following and spreading trends, news and ideas all over the world. As a result, microblog search has emerged as a new option for covering user information needs, especially with respect to timely events, news or trends. However users are frequently overloaded by the high rate of produced microblogging posts, which often carry no new information with respect to other similar posts. In this paper we propose a method that helps users effectively harvest information from a microblogging stream, by filtering out redundant data and maximizing diversity among the displayed information. We introduce microblog posts-specific diversification criteria and apply them on heuristic diversification algorithms. We implement the above methods into a prototype system that works with data from Twitter. The experimental evaluation, demonstrates the effectiveness of applying our problem specific diversification criteria, as opposed to applying plain content diversity on microblog posts.
机译:微博已成为重要的信息来源,是在世界范围内追踪和传播趋势,新闻和思想的媒介。结果,微博搜索已经成为满足用户信息需求的新选择,特别是在及时事件,新闻或趋势方面。但是,用户经常会因微博帖子产生率高而超载,相对于其他类似帖子,微博帖子通常没有新信息。在本文中,我们提出了一种方法,该方法可通过过滤掉冗余数据并最大化显示信息之间的多样性,来帮助用户从微博流中有效地收集信息。我们介绍了微博帖子特定的多元化标准,并将其应用于启发式多元化算法。我们将上述方法实施到可以处理Twitter数据的原型系统中。实验评估表明,应用我们特定于问题的多元化标准相对于在微博帖子上应用纯内容多样性是有效的。

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