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Efficiently Maintaining Structural Associations of Semistructured Data

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Advances in Informatics (PCI 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2563))

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Abstract

Semistructured data arise frequently in the Web or in data integration systems. Semistructured objects describing the same type of information have similar but not identical structure. Finding the common schema of a collection of semistructured objects is a very important task and due to the huge volume of such data encountered, data mining techniques have been employed. Maintenance of the discovered schema in case of updates, i.e., addition of new objects, is also a very important issue. In this paper, we study the problem of maintaining the discovered schema in the case of the addition of new objects. We use the notion of “negative borders” introduced in the context of mining association rules in order to efficiently find the new schema when objects are added to the database. We present experimental results that show the improved efficiency achieved by the proposed algorithm.

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Author information

Authors and Affiliations

  1. Department of Informatics, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece

    Dimitrios Katsaros

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  1. Dimitrios Katsaros
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Editor information

Editors and Affiliations

  1. Dept. of Informatics, Aristotle University, 54006, Thessaloniki, Greece

    Yannis Manolopoulos

  2. Dept. of Computer Science, University of Cyprus, P.O. Box 20537, 1678, Nicosia, Cyprus

    Skevos Evripidou  & Antonis C. Kakas  & 

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© 2003 Springer-Verlag Berlin Heidelberg

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Katsaros, D. (2003). Efficiently Maintaining Structural Associations of Semistructured Data. In: Manolopoulos, Y., Evripidou, S., Kakas, A.C. (eds) Advances in Informatics. PCI 2001. Lecture Notes in Computer Science, vol 2563. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-38076-0_8

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  • DOI: https://doi.org/10.1007/3-540-38076-0_8

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-07544-8

  • Online ISBN: 978-3-540-38076-4

  • eBook Packages: Springer Book Archive

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