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Integrating and Querying Parallel Leaf Shape Descriptions
Shenghui Wang1 and Jeff Z. Pan2
1School of Computer Science, University of Manchester, UK
2Department of Computing Science, University of Aberdeen, UK
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.
LNCS 4273, p. 668 ff.
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© Springer-Verlag Berlin Heidelberg 2006