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Partitioning and Merging an Index for Efficient XML Keyword Search  

Kim, Sung-Jin (서울대학교 전기컴퓨터공학부)
Lee, Hyung-Dong (서울대학교 전기컴퓨터공학부)
Kim, Hyoung-Joo (서울대학교 전기컴퓨터공학부)
Publication Information
Journal of KIISE:Databases / v.33, no.7, 2006 , pp. 754-765 More about this Journal
Abstract
In XML keyword search, a search result is defined as a set of the smallest elements (i.e., least common ancestors) containing all query keywords and a granularity of indexing is an XML element instead of a document. Under the conventional index structure, all least common ancestors produced by the combination of the elements, each of which contains a query keyword, are considered as a search result. In this paper, to avoid unnecessary operations of producing the least common ancestors and reduce query process time, we describe a way to construct a partitioned index composed of several partitions and produce a search result by merging those partitions if necessary. When a search result is restricted to be composed of the least common ancestors whose depths are higher than a given minimum depth, under the proposed partitioned index structure, search systems can reduce the query process time by considering only combinations of the elements belonging to the same partition. Even though the minimum depth is not given or unknown, search systems can obtain a search result with the partitioned index, which requires the same query process time to obtain the search result with non-partitioned index. Our experiment was conducted with the XML documents provided by the DBLP site and INEX2003, and the partitioned index could reduce a substantial amount of query processing time when the minimum depth is given.
Keywords
XML(eXtensible Markup Language); XML Keyword Search; Partitioned Index;
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