【摘 要】
：
This paper presents an effective keyword search method for data-centric extensive markup language (XML) documents.The method divides an XML document into compac
【机 构】
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Department of Computer Science and Technology
【基金项目】
：
国家高技术研究发展计划(863计划);the Basic Research Foundation of Tsinghua National Laboratory for Information Science and Technology (TNList);HP Labs Innovation Research Program
论文部分内容阅读
This paper presents an effective keyword search method for data-centric extensive markup language (XML) documents.The method divides an XML document into compact connected integral subtrees,called self-integral trees (Si-Trees),to capture the structural information in the XML document.The Si-Trees are generated based on a schema guide.Meaningful self-integral trees (MSI-Trees) are identified,which contain all or some of the input keywords for the keyword search in the XML documents.Indexing is used to accelerate the retrieval of MSI-Trees related to the input keywords.The MSI-Trees are ranked to identify the top-k results with the highest ranks.Extensive tests demonstrate that this method costs 10-100 ms to answer a keyword query,and outperforms existing approaches by 1-2 orders of magnitude.
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