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Query Approximation by Semantic Similarity in GeoPQL

  • Fernando Ferri
  • Anna Formica
  • Patrizia Grifoni
  • Maurizio Rafanelli
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4278)

Abstract

This paper proposes a method for query approximation in Geographical Information Systems. In our approach, queries are expressed by the Geographical Pictorial Query Language (GeoPQL), and query approximation is performed using WordNet, a lexical database for the English language available on the Internet. Due to the focus on geographical context, we address WordNetpartitiontaxonomies. If a concept contained in a query has no match in the database, the query is approximated using the immediate superconcepts and subconcepts in the WordNet taxonomy, and their related degrees of similarity. Semantic similarity is evaluated using the information content approach, which shows a higher correlation with human judgment than the traditional similarity measures.

Keywords

Semantic Similarity Lexical Database Entity Class Geographical Database Geographical Object 
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

  • Fernando Ferri
    • 1
  • Anna Formica
    • 2
  • Patrizia Grifoni
    • 1
  • Maurizio Rafanelli
    • 2
  1. 1.IRPPS-CNRRomeItaly
  2. 2.IASI-CNRRomeItaly

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