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Fuzzy View-Based Semantic Search

  • Markus Holi
  • Eero Hyvönen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4185)

Abstract

This paper presents a fuzzy version of the semantic view-based search paradigm. Our framework contributes to previous work in two ways: First, the fuzzification introduces the notion of relevance to view-based search by enabling the ranking of search results. Second, the framework makes it possible to separate the end-user’s views from content indexer’s taxonomies or ontologies. In this way, search queries can be formulated and results organized using intuitive categories that are different from the semantically complicated indexing concepts. The fuzziness is the result of allowing more accurate weighted annotations and fuzzy mappings between search categories and annotation ontologies. A prototype implementation of the framework is presented and its application to a data set in a semantic eHealth portal discussed.

Keywords

Membership Function Description Logic Membership Degree Fuzzy Mapping Search Item 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Markus Holi
    • 1
  • Eero Hyvönen
    • 1
  1. 1.Helsinki University of Technology (TKK), Media Technology and University of HelsinkiFinland

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