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The Model Research of FAQ Answering System Based on Concept

机译:基于概念的常见问题解答系统模型研究

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At present, the FAQ (Frequently-Asked Question) answering system cannot understand the user's questions at the concept level, so its efficiency needs to be improved. In this paper, a model of FAQ answering system based on concept is proposed. The system model consists of three components, which are concept-based preprocessing, extraction of question-answer pairs, and concept-based matching of sentences. On the one hand, the model proposes an index-based extracting method of question-answering pairs, to combine the extraction with the index mechanism for improving the speed of extraction. On the other hand, the model expands the user's question at the concept level, and proposes a concept based matching method between sentences, to match the user's question with the question-answering pairs. The concept based matching method concerns the synonymous meanings between sentences at the concept level. In addition, the experimental result shows the matching method is an efficient method.
机译:目前,FAQ(FAQ)回答系统在概念层面上还不能理解用户的问题,因此需要提高效率。本文提出了一种基于概念的常见问题解答系统模型。系统模型由三个组件组成,分别是基于概念的预处理,问题-答案对的提取以及基于概念的句子匹配。一方面,该模型提出了一种基于索引的问答对提取方法,将提取与索引机制结合起来,提高了提取速度。另一方面,该模型在概念级别上扩展了用户的问题,并提出了句子之间基于概念的匹配方法,以将用户的问题与问答对进行匹配。基于概念的匹配方法在概念级别涉及句子之间的同义词含义。另外,实验结果表明匹配方法是一种有效的方法。

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