Topic relatedness in evaluative information extraction

T. Kawada, Tetsuji Nakagawa, Kentaro Inui, S. Kurohashi
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引用次数: 1

Abstract

The task of extracting opinions/evaluations related to a given topic from a large number of documents such as Web documents is crucial for developing an automatic evaluation finding system, which can handle a wide variety of topics as input. In this paper, we discuss the topic relatedness of extracted evaluation through analysis of a corpus we developed. We suggest here that the semantic relationship between the target of each extracted evaluation and a given topic helps in judging topic relatedness. In addition, we point out other factors that are beyond the analysis of topic-target relations for judging the topic relatedness of evaluation.
评价信息提取中的主题相关性
从大量文档(如Web文档)中提取与给定主题相关的意见/评估的任务对于开发自动评估查找系统至关重要,该系统可以处理各种主题作为输入。在本文中,我们通过分析我们开发的语料库来讨论抽取评价的主题相关性。我们在此建议,每个提取评价的目标与给定主题之间的语义关系有助于判断主题相关性。此外,我们还指出了其他超出话题-目标关系分析的因素来判断评价的话题相关性。
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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