Extracting partition statistics from semistructured data

John N. Wilson, Richard Gourlay, Robert Japp, Mathias Neumüller

Research output: Contribution to conference › Paper

2 Citations (Scopus)
35 Downloads (Pure)

Abstract

The effective grouping, or partitioning, of semistructured data is of fundamental importance when providing support for queries. Partitions allow items within the data set that share common structural properties to be identified efficiently. This allows queries that make use of these properties, such as branching path expressions, to be accelerated. Here, we evaluate the effectiveness of several partitioning techniques by establishing the number of partitions that each scheme can identify over a given data set. In particular, we explore the use of parameterised indexes, based upon the notion of forward and backward bisimilarity, as a means of partitioning semistructured data; demonstrating that even restricted instances of such indexes can be used to identify the majority of relevant partitions in the data.
Original languageEnglish
Pages497-506
Number of pages9
Publication statusPublished - 4 Sep 2006
Event17th International Workshop on Database and Expert Systems Applications (DEXA 2006) - Krakow, Poland
Duration: 4 Sep 2006 → 8 Sep 2006

Conference

Conference17th International Workshop on Database and Expert Systems Applications (DEXA 2006)
CityKrakow, Poland
Period4/09/06 → 8/09/06

Fingerprint

Structural properties
Statistics

Keywords

  • semistructured data
  • data management
  • partitions
  • indexes
  • statistics

Cite this

Wilson, J. N., Gourlay, R., Japp, R., & Neumüller, M. (2006). Extracting partition statistics from semistructured data. 497-506. Paper presented at 17th International Workshop on Database and Expert Systems Applications (DEXA 2006), Krakow, Poland, .
Wilson, John N. ; Gourlay, Richard ; Japp, Robert ; Neumüller, Mathias. / Extracting partition statistics from semistructured data. Paper presented at 17th International Workshop on Database and Expert Systems Applications (DEXA 2006), Krakow, Poland, .9 p.
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Wilson, JN, Gourlay, R, Japp, R & Neumüller, M 2006, 'Extracting partition statistics from semistructured data' Paper presented at 17th International Workshop on Database and Expert Systems Applications (DEXA 2006), Krakow, Poland, 4/09/06 - 8/09/06, pp. 497-506.

Extracting partition statistics from semistructured data. / Wilson, John N.; Gourlay, Richard; Japp, Robert; Neumüller, Mathias.

2006. 497-506 Paper presented at 17th International Workshop on Database and Expert Systems Applications (DEXA 2006), Krakow, Poland, .

Research output: Contribution to conference › Paper

TY - CONF

T1 - Extracting partition statistics from semistructured data

AU - Wilson, John N.

AU - Gourlay, Richard

AU - Japp, Robert

AU - Neumüller, Mathias

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AB - The effective grouping, or partitioning, of semistructured data is of fundamental importance when providing support for queries. Partitions allow items within the data set that share common structural properties to be identified efficiently. This allows queries that make use of these properties, such as branching path expressions, to be accelerated. Here, we evaluate the effectiveness of several partitioning techniques by establishing the number of partitions that each scheme can identify over a given data set. In particular, we explore the use of parameterised indexes, based upon the notion of forward and backward bisimilarity, as a means of partitioning semistructured data; demonstrating that even restricted instances of such indexes can be used to identify the majority of relevant partitions in the data.

KW - semistructured data

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UR - http://www.cis.strath.ac.uk/research/publications/papers/strath_cis_publication_1545.pdf

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Wilson JN, Gourlay R, Japp R, Neumüller M. Extracting partition statistics from semistructured data. 2006. Paper presented at 17th International Workshop on Database and Expert Systems Applications (DEXA 2006), Krakow, Poland, .

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