揭示事件及其特征项之间的关联

Shin-ya Sato, Masami Takahashi, Tetsuya Nakamura, M. Matsuo
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引用次数: 0

摘要

我们提出了一个新问题,即发现我们日常生活中的事件与其特征项目之间的联系,例如(万圣节,南瓜)和(圣诞节,烟囱)。为了解决这个问题,我们采用了一种类似于现有事件检测研究的方法,即通过检测文档流中相关术语的出现频率爆发来发现事件,其中术语(项)与发现的事件相关联。我们从Web上可用的博客条目中提取事件,而之前的研究主要使用新闻文章作为文档流。博客条目显示出与新闻文章具有完全不同的特征。考虑到这一事实,我们开发了一种方法,通过集成可以处理和利用博客数据特征的现有技术来发现关联。我们通过实际数据的实验验证了所提出的方法的有效性。
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Revealing Associations between Events and Their Characteristic Items
We pose a new problem of discovering associations between events in our daily lives and their characteristic items, such as (Halloween, pumpkin) and (Christmas, chimney). To solve the problem, we dopted an approach similar to that of existing research on event detection, which tries to discover events by detecting bursts of occurrence frequency of a relevant term in a document stream, where the term (item) is associated with the discovered event. We extracted events from blog entries available on the Web, while the previous studies mostly used news articles as document streams. Blog entries are shown to have quite different characteristics to news articles. Considering this fact, we developed a method for discovering the associations by integrating existing techniques that can handle and take advantage of the characteristics of blog data. We verified through experiments using actual data that the proposed approach works quite well.
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