Event-based summarization of news articles

Authors : Feride Savaroğlu TABAK, Vesile EVRİM

Pages : 850-864

Doi:10.3906/elk-1904-98

View : 23 | Download : 12

Publication Date : 0000-00-00

Article Type : Research Paper

Abstract :In recent years, with the increase of available digital information on the Web, the time needed to find relevant information is also increased. Therefore, to reduce the time spent on searching, research on automatic text summarization has gained importance. The proposed summarization process is based on event extraction methods and is called an event-based extractive single-document summarization. In this method, the important features of event extraction and summarization methods are analyzed and combined together to extract the summaries from single-source news documents. Among the tested features, six features are found to be the most effective in constructing good summaries. The constructed summaries are tested on benchmark Document Understanding Conferences 2001 and 2002 datasets, and the results outperformed most of the other well-known summarization methods.
Keywords : Event based summarization, event extraction, feature selection, single text summarization, extractive summarization