维基百科挖掘大规模日本协会词库建设

Kotaro Nakayama, Masahiro Ito, T. Hara, S. Nishio
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引用次数: 6

摘要

维基百科,一个庞大的基于网络的词典,是一个令人印象深刻的知识提取语料库。我们已经证明了维基百科可以用来构建英语关联词库,我们的链接结构挖掘方法在这方面是非常有效的。然而,我们想知道如何将这种方法应用到其他语言中,以及这些语言的需求、差异和特点是什么。如今,维基百科支持英语、德语、法语、波兰语和日语等250多种语言。在亚洲语言中,日语维基百科是维基百科中最大的语料库。因此,在本研究中,我们分析了维基百科中所有的日语文章,并构建了一个庞大的日语关联词库。在构建同义词库之后,我们意识到它根据语言和文化表现出几个令人印象深刻的特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Wikipedia Mining for Huge Scale Japanese Association Thesaurus Construction
Wikipedia, a huge scale Web-based dictionary, is an impressive corpus for knowledge extraction. We already proved that Wikipedia can be used for constructing an English association thesaurus and our link structure mining method is significantly effective for this aim. However, we want to find out how we can apply this method to other languages and what the requirements, differences and characteristics are. Nowadays, Wikipedia supports more than 250 languages such as English, German, French, Polish and Japanese. Among Asian languages, the Japanese Wikipedia is the largest corpus in Wikipedia. In this research, therefore, we analyzed all Japanese articles in Wikipedia and constructed a huge scale Japanese association thesaurus. After constructing the thesaurus, we realized that it shows several impressive characteristics depending on language and culture.
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