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An adaptable Question-Answer System using match of multi-sphere knowledge

机译:利用多领域知识匹配的适应性问答系统

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For a performance enhancement of the current a QAS(Question-Answer System) and web search, the adaptable semantic decision is important which support expression of natural language and meaning of a input sentence about UIDD(User Information Demand Description) is a difficult situation natural language and adaptable semantic decision in a sentence up to now. For overcome these problems, a various research was attempted that decided for search result about UIDD based on information retrieval model, and a lot of a QAS and search engine like Google applied which was currently proposed, but it is difficult to provide the retrieval results that determine flexibly a similarity of meaning. Therefore, this study, match knowledge which use the semantic inference rule which expressed knowledge in multi-sphere knowledge, and inferenced knowledge combine with n-ary representation-based ontology by weight, then determine various semantic similarity about a vocabulary in UIDD. As decide on semantic similarity, we propose an approach which presented a most adaptable answer that input a question to a QAS. And a proposed approach-based, we implement a QAS which service a prescription regarding a symptom and inform a foot reflective point to user. An experiment result of implement system, determine adaptable to a semantic similarity of a vocabulary regarding input query sentence, and show a stable query result, and a proposal approach demonstrated that we were effective.
机译:对于当前的QAS(问答系统)和Web搜索的性能增强而言,适应性语义决策非常重要,它支持自然语言的表达和有关UIDD(用户信息需求描述)的输入句子的含义,这是自然而然的困难情况语言和句子中的适应性语义决定。为了克服这些问题,试图进行各种研究以基于信息检索模型来确定关于UIDD的搜索结果,并且目前提出了许多像谷歌一样应用的QAS和搜索引擎,但是难以提供能够提供搜索结果的搜索结果。灵活地确定含义的相似性。因此,本研究对使用多领域知识中表达知识的语义推理规则的知识进行匹配,并将推理后的知识与基于n元表示的本体按权重相结合,然后确定UIDD中某个词汇的各种语义相似性。在决定语义相似性时,我们提出了一种方法,该方法提供了最适合的答案,该问题向QAS输入了一个问题。在提出的基于方法的基础上,我们实施了QAS,该服务为有关症状的处方服务,并向用户告知足部反射点。实施系统的实验结果,确定适用于输入查询词的词汇语义相似度,并显示稳定的查询结果,提出的方法证明了我们的有效性。

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