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Text Information Retrieval Based on Concept Semantic Similarity

机译:基于概念语义相似度的文本信息检索

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In this paper, an improved method of calculating ontology semantic similarity is proposed to enhance the information retrieval recall and precision. To filter out the document which have smaller related degree with original query, the scores of search results document is re-calculated by use of ontology semantic similarity. A new definition of the iterative query expansion parameters is put forward which can reduce the number of expansion and further improve the efficiency of the query. The use of open source tools for text semantic retrieval test, i.e., Jena and Lucene, has verified the feasibility and effectiveness of the proposed method.
机译:本文提出了一种改进的本体语义相似度计算方法,以提高信息检索的查全率和查准率。为了过滤出与原始查询关联度较小的文档,利用本体语义相似度对搜索结果文档的分数进行重新计算。提出了迭代查询扩展参数的新定义,可以减少扩展次数,进一步提高查询效率。使用开源工具进行文本语义检索测试,即Jena和Lucene,已验证了该方法的可行性和有效性。

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