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The Ontology of Natural Language Processing

机译:自然语言处理的本体

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In this paper, we describe our proposed methodology for constructing an ontology of natural language processing (NLP). We use a semi-automatic method; a combination of rule-based and machine learning techniques; to construct and populate an ontology with bilingual (English-Persian) concept labels (lexicon) and evaluate it manually. This methodology results in a complete ontology in the natural language processing domain with 887 concepts, 88 relations, and 71 features. The built ontology is populated with near 36000 NLP related papers and 32000 authors, and about 201000 "is_Related_to", 83500 "is_Author_of", and 29000 "Presented_in" relations. The instantiation is done to enable applications find experts, publications and institutions related to various topics in NLP field.
机译:在本文中,我们描述了我们提出的用于构建自然语言处理(NLP)本体的方法。我们使用半自动方法;基于规则和机器学习技术的结合;用双语(英语-波斯语)概念标签(词典)构建和填充本体,并对其进行手动评估。这种方法在自然语言处理领域产生了一个完整的本体,具有887个概念,88个关系和71个特征。构建的本体填充了近36000个NLP相关论文和32000位作者,以及大约201000个“ is_Related_to”,83500个“ is_Author_of”和29000个“ Presented_in”关系。进行实例化是为了使应用程序可以找到与NLP领域的各个主题相关的专家,出版物和机构。

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