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Inferences in natural language understanding

机译:自然语言理解的推论

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摘要

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.
机译:本文介绍了语言理解的亚马逊模糊方法。作者在两个基本推论方面讨论了自然语言理解的问题:1)案文周围隐含知识的推理; 2)从句子的明确上下文中扣除。采用模糊推理和连接技术,以产生正确的结果。它们足够灵活,可以在自然语言环境中工作,其特征在于几乎无限的变化。首先,语言含义以亚胚微泡编码。模糊规则矩阵中的模糊推理技术用于捕获文本中的周围知识。最后,采用模糊统一过程来形成相干结构并理解上下文。

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