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Research on XML Keyword Query Method Based on Semantic

机译:基于语义的XML关键字查询方法研究

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摘要

In this paper, we study the problem of effective keyword search over XML documents, Keyword search for smallest lowest common ancestor(SLCA) in XML data has recently been proposed as a meaningful way to identify interesting data nodes in XML data where their sub trees contain an input set of keywords. XML retrieval technology has been concerned widely by information retrieval researchers. XML data contains rich semantic information, but most of query methods can't make full use of the semantic information. There will be missed case if there is no enough semantic information. This paper proposed a new XML keyword query algorithm based on semantic(SKSA) to solve the question above. The algorithm takes full use of the node semantic information based on structural semantic. The same or similar results will be returned to users if there is no the keyword in XML document, which avoids the missed case. The test experiment result on the real XML data sets shows that SKSA has higher recall rate, and can match the user's query intention better.
机译:在本文中,我们研究了XML文档的有效关键字搜索问题,最近已经提出了XML数据中最小的最低公共祖先(SLCA)的关键字搜索是一种有意义的方法,以识别其子树包含的XML数据中有趣的数据节点输入集关键字。 XML检索技术被信息检索研究人员广泛关注。 XML数据包含丰富的语义信息,但大多数查询方法都无法充分利用语义信息。如果没有足够的语义信息,会错过案例。本文提出了一种基于语义(SKSA)的新XML关键字查询算法来解决上述问题。该算法采用基于结构语义的节点语义信息充分利用。如果XML文档中没有关键字,则将返回相同或相似的结果,这避免了错过的情况。测试实验结果对实际XML数据集显示SKSA具有更高的召回率,并且可以更好地匹配用户的查询意图。

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