基于语言真值概念格的隐性知识挖掘算法

2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE) Pub Date : 2012-01-15 DOI:10.1109/ISKE.2015.59

Li Yang, Yuhui Wang, Yang Xu

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引用次数: 2

摘要

自然语言处理是人工智能领域的重要研究方向之一，自然语言表达的隐性知识是研究热点。为了给隐性知识的挖掘提供一个数学工具，我们建立了一个处理自然语言的六元语言真值概念格的具体模型，并通过结构一致性引入了一种隐性知识的挖掘算法。具体地说，我们利用属性来描述知识，提出了六元语言真值对象、隐性语境和同型语境来表征隐性知识，并研究了隐性知识形成的充分必要条件。分别给出了语言真值同型上下文的生成算法和六元语言真值概念格的构造算法。

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Tacit Knowledge Mining Algorithm Based on Linguistic Truth-Valued Concept Lattice

Natural language processing is one of the important research in the field of artificial intelligence, and tacit knowledge expressed by natural language is the research hotspot. In order to provide a mathematical tool for mining tacit knowledge, we establish a concrete model of 6-ary linguistic truth-valued concept lattice to deal with natural language and introduce a mining algorithm of tacit knowledge through the structure consistency. Specifically, we utilize the attributes to depict knowledge, propose the 6-ary linguistic truth-valued object tacit context and homotype context to characterize tacit knowledge, and research the necessary and sufficient conditions of forming tacit knowledge. We respectively give the generating algorithm of the linguistic truth-valued homotype context and the constructing algorithm the 6-ary linguistic truth-valued concept lattice.

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2015 10th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)

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