Event recognition from information-linkage based using phrase tree traversal

R. Sukhahuta, Chadchai Sukanun
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Abstract

In this paper we present an approach to extracting significant events from digital documents. OpenNLP syntactical parser for English is used for generating parse trees from the sentences, followed by the extraction of events from the parse trees using tree traversal algorithms. The extraction system is developed and tested on 50 sentences from terrorism documents of The Federation of American Scientists (FAS). The results showed that with this technique we can achieve high recall and precision yielding accuracy of 89.68 recall and 78.44 precision with an overall performance of 83.66 in term of F-measure.
基于短语树遍历的信息链接事件识别
在本文中,我们提出了一种从数字文档中提取重要事件的方法。OpenNLP英语语法解析器用于从句子生成解析树,然后使用树遍历算法从解析树中提取事件。该提取系统以美国科学家联合会(FAS)恐怖主义文件中的50句话为对象进行了开发和测试。结果表明,该方法具有较高的查全率和查准率,查全率为89.68,查准率为78.44,F-measure的综合性能为83.66。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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