Incremental Clustering of News Reports
Incremental Clustering of News Reports
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DOI：
10.3390/a5030364
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发表时间：
2012-09-01
期刊：
影响因子：
2.3
通讯作者：
Staff, Christopher
中科院分区：
文献类型：
--
作者：
Azzopardi, Joel;Staff, Christopher
当事件发生在真实的世界中时，在事件发生的几分钟内，描述该事件的大量新闻报道开始出现在不同的新闻网站上。这可能会导致用户获得大量信息，并且可能需要自动化流程来帮助管理这些信息。在本文中，我们描述了一个聚类系统，它可以将来自不同来源的新闻报道聚类为以事件为中心的聚类，描述同一事件的一组新闻报道。用户可以识别任何RSS提要作为他/她想接收的新闻来源，我们的聚类系统可以在收到来自不同RSS提要的报告时对其进行聚类，而无需事先知道聚类的数量。我们的集群系统被设计成在在线增量环境中运行良好。在评估我们的系统时，我们发现我们的系统在执行细粒度聚类时表现非常好，但是在执行粗粒度聚类时表现相当差
When an event occurs in the real world, numerous news reports describing this event start to appear on different news sites within a few minutes of the event occurrence. This may result in a huge amount of information for users, and automated processes may be required to help manage this information. In this paper, we describe a clustering system that can cluster news reports from disparate sources into event-centric clustersi.e., clusters of news reports describing the same event. A user can identify any RSS feed as a source of news he/she would like to receive and our clustering system can cluster reports received from the separate RSS feeds as they arrive without knowing the number of clusters in advance. Our clustering system was designed to function well in an online incremental environment. In evaluating our system, we found that our system is very good in performing fine-grained clustering, but performs rather poorly when performing coarser-grained clustering