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Knowledge representation: Predicate logic implementation using sentence-type for natural languages

机译:知识表示:自然语言使用句子类型的谓词逻辑实现

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摘要

Representing the content of the text is really an important issue of knowledge representation. Natural language processing (NLP) is a field of computer science, artificial intelligence, and linguistics concerned with the interactions between computers and human languages. It processes the data through lexical analysis, Syntax analysis, Semantic analysis, Discourse processing, Pragmatic analysis. This paper compares various knowledge representation schemes. The algorithm in this paper splits the English sentences into phrases and then represents these in predicate logic by considering the types of sentences (Simple, Interrogative, Exclamatory, Passive etc.). The algorithm has been tested on real sentences of English. The algorithm has achieved an accuracy of 75%. This representation would be used in future for Semantic based Text summarization.
机译:表示文本的内容确实是知识表示的重要问题。自然语言处理(NLP)是与计算机和人类语言之间的交互相关的计算机科学,人工智能和语言学领域。它通过词法分析,语法分析,语义分析,语篇处理,语用分析来处理数据。本文比较了各种知识表示方案。本文中的算法将英语句子分为短语,然后通过考虑句子的类型(简单,疑问句,感叹,被动等)以谓词逻辑表示它们。该算法已在英语的真实句子中进行了测试。该算法已达到75%的精度。此表示将在将来用于基于语义的文本摘要。

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