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A Semantic Vector Retrieval Model for Desktop Documents

机译:桌面文档的语义矢量检索模型

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摘要

The paper provides a semantic vector retrieval model for desktop documents based on the ontology. Comparing with traditional vector space model, the semantic model using semantic and ontology technology to solve several problems that traditional model could not overcome such as the shortcomings of weight computing based on statistical method, the expression of semantic relations between different keywords, the description of document semantic vectors and the similarity calculating, etc. Finally, the experimental results show that the retrieval ability of our new model has significant improvement both on recall and precision.
机译:本文提供了一种基于本体的桌面文档语义向量检索模型。与传统向量空间模型相比,该语义模型利用语义和本体技术解决了传统模型无法克服的若干问题,例如基于统计方法的权重计算的缺点,不同关键词之间语义关系的表达,文档描述等。最后,实验结果表明,新模型的检索能力在查全率和查准率上都有明显的提高。

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