Associative and spatial relationships in thesaurus-based retrieval

Alani, Harith; Jones, Christopher and Tudhope, Douglas (2000). Associative and spatial relationships in thesaurus-based retrieval. In: 4th European Conference on Digital Libraries (ECDL) (Borbinha, Jose and Baker, Thomas eds.), 18-20 Sep 2000, Lisbon, Portugal, Springer, pp. 45–58.

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URL:	http://www.informatik.uni-trier.de/~ley/db/conf/er...
DOI (Digital Object Identifier) Link:	https://doi.org/10.1007/3-540-45268-0_5
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Abstract

The OASIS (Ontologically Augmented Spatial Information System) project explores terminology systems for thematic and spatial access in digital library applications. A prototype implementation uses data from the Royal Commission on the Ancient and Historical Monuments of Scotland, together with the Getty AAT and TGN thesauri. This paper describes its integrated spatial and thematic schema and discusses novel approaches to the application of thesauri in spatial and thematic semantic distance measures. Semantic distance measures can underpin interactive and automatic query expansion techniques by ranking lists of candidate terms. We first illustrate how hierarchical spatial relationships can be used to provide more flexible retrieval for queries incorporating place names in applications employing online gazetteers and geographical thesauri. We then employ a set of experimental scenarios to investigate key issues affecting use of the associative (RT) thesaurus relationships in semantic distance measures. Previous work has noted the potential of RTs in thesaurus search aids but the problem of increased noise in result sets has been emphasised. Specialising RTs allows the possibility of dynamically linking RT type to query context. Results presented in this paper demonstrate the potential for filtering on the context of the RT link and on subtypes of RT relationships.

Item Type:	Conference or Workshop Item
Copyright Holders:	2000 Springer-Verlag
ISBN:	3-540-41023-6, 978-3-540-41023-2
ISSN:	0302-9743
Academic Unit/School:	Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi) Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group:	Centre for Research in Computing (CRC)
Item ID:	20069
Depositing User:	Harith Alani
Date Deposited:	15 Apr 2010 09:59
Last Modified:	10 Dec 2018 03:18
URI:	http://oro.open.ac.uk/id/eprint/20069
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