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A Method for Judging Illogical Discourse Based on Concept Association and Common-Sense Judgment

机译:一种基于概念协会和常识判断的判断不合逻辑话语的方法

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In recent years, research into natural language processing for implementing natural discourse has attracted considerable attention. However, up to now, research into natural language processing has focused mainly on discourse processing for certain limited objectives and under specific conditions, with emphasis on the superficial formation of sentences. The understanding of the user-generated words is constrained by the size of the constructed knowledge base and the quality of actual data collected. Overcoming this limitation requires the capability to autonomously generate discourse sentences using a computer. However, there is a risk that the generation of response sentences by a computer results in illogical word combinations caused by the mechanical combination of words. To avoid this risk, the capability of detecting illogical word combinations is needed. This paper proposes a technique for judging illogical word combinations by creating a knowledge model of human discourse and words.
机译:近年来,研究实施自然话语的自然语言处理引起了相当大的关注。然而,截至目前,研究自然语言处理主要集中在某些有限目标和特定条件下的话语加工,重点是句子的肤浅形成。对用户生成的单词的理解受到构建知识库的大小和收集的实际数据的质量的约束。克服此限制需要使用计算机自主地生成话语句子的功能。然而,有一种风险,计算机通过计算机的反应句子产生由单词机械组合引起的不合逻辑组合。为避免这种风险,需要检测不合逻辑单词组合的能力。本文提出了一种通过创建人类话语和词语知识模型来判断不合逻辑词组的技术。

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