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Knowledge Extraction Based on Sentence Matching and Analyzing

机译:基于句子匹配和分析的知识提取

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Knowledge Extraction extracts knowledge from documents by analyzing document contents, then markups knowledge attribute and stores them into knowledge base. This paper discusses definition of knowledge extraction at first, then presents goal, key technique, application and system architecture of knowledge extraction based on sentence matching and analyzing. The system identifies new sentences in a paper, and makes an analysis of the sentences from internal structure and subject semantics. Then justify knowledge metadata by analyzing association among sentences and pragmatic of the whole paper. At last, allocates knowledge attribute tag for extracted knowledge, such as definition, historic development, characteristics, key technique, classification, application and development trend in the future. Knowledge extraction based on sentence matching and analyzing can not only justify the academic copying or scientific citation automatically, as well as make a document reviewed automatically, but also achieve a conversion on analysis from paper and chapter to sentence and paragraph, which can induce a revolution in knowledge organization and management. Therefore, the study has far-reaching theoretical significance and wide application.
机译:知识提取通过分析文档内容来提取文档的知识,然后将知识属性标记并将其存储到知识库中。本文首先讨论了知识提取的定义,基于句子匹配和分析,提出了知识提取的目标,关键技术,应用和系统架构。该系统在纸上识别新句子,并分析了内部结构和主语语义的句子。然后通过分析句子的关联和整个纸张的务实的关联证明知识元数据。最后,为提取的知识分配知识属性标签,例如未来的定义,历史开发,特征,关键技术,分类,应用和发展趋势。基于句子匹配和分析的知识提取不仅可以自动地证明学术复印或科学引文,以及自动审查文件,还可以在纸张和章节和段落中进行分析转换,这可以引起革命在知识组织和管理中。因此,该研究具有深远的理论意义和广泛的应用。

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