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Integrating and Querying Parallel Leaf Shape Descriptions

  • Shenghui Wang
  • Jeff Z. Pan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4273)

Abstract

Information integration and retrieval have been important problems for many information systems — it is hard to combine new information with any other piece of related information we already possess, and to make them both available for application queries. Many ontology-based applications are still cautious about integrating and retrieving information from natural language (NL) documents, preferring structured or semi-structured sources. In this paper, we investigate how to use ontologies to facilitate integrating and querying information on parallel leaf shape descriptions from NL documents. Our approach takes advantage of ontologies to precisely represent the semantics in shape description, to integrates parallel descriptions according to their semantic distances, and to answer shape-related species identification queries. From this highly specialised domain, we learn a set of more general methodological rules, which could be useful in other domains.

Keywords

Leaf Shape Information Integration Shape Description Semantic Distance Complex Description 
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

  • Shenghui Wang
    • 1
  • Jeff Z. Pan
    • 2
  1. 1.School of Computer ScienceUniversity of ManchesterUK
  2. 2.Department of Computing ScienceUniversity of AberdeenUK

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