Enterprise Data Classification Using Semantic Web Technologies

  • David Ben-David
  • Tamar Domany
  • Abigail Tarem
Conference paper

DOI: 10.1007/978-3-642-17749-1_5

Volume 6497 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Ben-David D., Domany T., Tarem A. (2010) Enterprise Data Classification Using Semantic Web Technologies. In: Patel-Schneider P.F. et al. (eds) The Semantic Web – ISWC 2010. ISWC 2010. Lecture Notes in Computer Science, vol 6497. Springer, Berlin, Heidelberg

Abstract

Organizations today collect and store large amounts of data in various formats and locations. However they are sometimes required to locate all instances of a certain type of data. Good data classification allows marking enterprise data in a way that enables quick and efficient retrieval of information when needed. We introduce a generic, automatic classification method that exploits Semantic Web technologies to assist in several phases in the classification process; defining the classification requirements, performing the classification and representing the results. Using Semantic Web technologies enables flexible and extensible configuration, centralized management and uniform results. This approach creates general and maintainable classifications, and enables applying semantic queries, rule languages and inference on the results.

Keywords

Semantic Techniques RDF Classification modeling 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • David Ben-David
    • 1
  • Tamar Domany
    • 2
  • Abigail Tarem
    • 2
  1. 1.Technion – Israel Institute of TechnologyHaifaIsrael
  2. 2.IBM Research – HaifaHaifaIsrael