Inferences in natural language understanding

S.W.K. Chan
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引用次数: 11

Abstract

This paper presents a subsymbolic fuzzy approach to language understanding. The author addresses the issue of natural language understanding in terms of two fundamental inferences: 1) the reasoning of implicit knowledge surrounding the text; and 2) the deduction from the explicit context of the sentences. Fuzzy reasoning and connectionist techniques are employed in order to yield right results. They are flexible enough to work in a natural language environment which is characterized by almost infinite variability. Firstly, linguistic meanings are encoded in subsymbolic microfeatures. A technique of fuzzy reasoning in a fuzzy rule matrix is used to capture the surrounding knowledge in the text. Finally, a fuzzy unification process is employed to form a coherent structure and comprehend the context.<>
自然语言理解中的推理
本文提出了一种亚符号模糊语言理解方法。作者从两个基本推论来解决自然语言理解的问题:1)围绕文本的隐性知识推理;2)从句子的明确语境中推断。为了得到正确的结果,采用了模糊推理和联结技术。它们足够灵活,可以在以几乎无限可变性为特征的自然语言环境中工作。首先,将语言意义编码为亚符号微特征。采用模糊规则矩阵中的模糊推理技术捕获文本中的周围知识。最后,采用模糊统一过程形成连贯的结构和理解上下文。
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