A new structure for accelerating Xpath location steps

Yaokai Feng; Akifumi Makinouchi

doi:10.1007/11775300_5

A new structure for accelerating Xpath location steps

Yaokai Feng, Akifumi Makinouchi

Real world robotics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Multidimensional indices have been successfully introduced to the field of querying on XML data. Using R*-tree, T. Grust proposed an interesting method to support all XPath axes. In that method, each node of an XML document is labeled with a five-dimensional descriptor. All the nodes of the XML document are mapped to a point set in a five-dimensional space. T. Grust made it clear that each of the XPath axes can be implemented by a range query in the above five-dimensional space. Thus, R*-tree can be used to improve the query performance for XPath axes. However, according to our investigations, most of the range queries for the XPath axes are partially-dimensional range queries. That is, the number of query dimensions in each of the range queries is less than five, although the R*-tree is built in the five-dimensional space. If the existing multidimensional indices are used for such range queries, then a great deal of information that is irrelevant to the queries also has to be read from disk. Based on this observation, a new multidimensional index structure (called Adaptive R*-tree) is proposed in this paper to support the XPath axes more efficiently.

Original language	English
Title of host publication	Advances in Web-Age Information Management - 7th International Conference, WAIM 2006, Proceedings
Publisher	Springer Verlag
Pages	49-60
Number of pages	12
ISBN (Print)	3540352252, 9783540352259
DOIs	https://doi.org/10.1007/11775300_5
Publication status	Published - Jan 1 2006
Event	7th International Conference on Advances in Web-Age Information Management, WAIM 2006 - Hong Kong, China Duration: Jun 17 2006 → Jun 19 2006

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4016 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	7th International Conference on Advances in Web-Age Information Management, WAIM 2006
Country	China
City	Hong Kong
Period	6/17/06 → 6/19/06

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/11775300_5

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Feng, Y., & Makinouchi, A. (2006). A new structure for accelerating Xpath location steps. In Advances in Web-Age Information Management - 7th International Conference, WAIM 2006, Proceedings (pp. 49-60). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4016 LNCS). Springer Verlag. https://doi.org/10.1007/11775300_5

A new structure for accelerating Xpath location steps. / Feng, Yaokai; Makinouchi, Akifumi.

Advances in Web-Age Information Management - 7th International Conference, WAIM 2006, Proceedings. Springer Verlag, 2006. p. 49-60 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4016 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Feng, Y & Makinouchi, A 2006, A new structure for accelerating Xpath location steps. in Advances in Web-Age Information Management - 7th International Conference, WAIM 2006, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4016 LNCS, Springer Verlag, pp. 49-60, 7th International Conference on Advances in Web-Age Information Management, WAIM 2006, Hong Kong, China, 6/17/06. https://doi.org/10.1007/11775300_5

Feng Y, Makinouchi A. A new structure for accelerating Xpath location steps. In Advances in Web-Age Information Management - 7th International Conference, WAIM 2006, Proceedings. Springer Verlag. 2006. p. 49-60. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/11775300_5

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