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Extracting partition statistics from semistructured data

Wilson, J.N. and Gourlay, R. and Japp, R. and Neumüller, M. (2006) Extracting partition statistics from semistructured data. In: 17th International Workshop on Database and Expert Systems Applications (DEXA 2006), 2006-09-04 - 2006-09-08, Krakow, Poland.

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    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.

    Item type: Conference or Workshop Item (Paper)
    ID code: 2387
    Keywords: semistructured data, data management, partitions, indexes, statistics, Electronic computers. Computer science
    Subjects: Science > Mathematics > Electronic computers. Computer science
    Department: Faculty of Science > Computer and Information Sciences
    Related URLs:
      Depositing user: Strathprints Administrator
      Date Deposited: 22 Jan 2007
      Last modified: 20 Jul 2013 21:52
      URI: http://strathprints.strath.ac.uk/id/eprint/2387

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