Meštrović, A. and Calì, Andrea (2017) An ontology-based approach to information retrieval. In: Calì, Andrea and Gorgan, D. and Ugarte, M. (eds.) Semantic Keyword-Based Search on Structured Data Sources. Lecture Notes in Computer Science 10151. Berlin, Germany: Springer, pp. 150-156. ISBN 9783319536392.
Abstract
We define a general framework for ontology-based information retrieval (IR). In our approach, document and query expansion rely on a base taxonomy that is extracted from a lexical database or a Linked Data set (e.g. WordNet, Wiktionary etc.). Each term from a document or query is modelled as a vector of base concepts from the base taxonomy. We define a set of mapping functions which map multiple ontological layers (dimensions) onto the base taxonomy. This way, each concept from the included ontologies can also be represented as a vector of base concepts from the base taxonomy. We propose a general weighting schema which is used for the vector space model. Our framework can therefore take into account various lexical and semantic relations between terms and concepts (e.g. synonymy, hierarchy, meronymy, antonymy, geo-proximity, etc.). This allows us to avoid certain vocabulary problems (e.g. synonymy, polysemy) as well as to reduce the vector size in the IR tasks.
Metadata
| Item Type: | Book Section |
|---|---|
| School: | Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences |
| Research Centres and Institutes: | Data Analytics, Birkbeck Institute for |
| Depositing User: | Administrator |
| Date Deposited: | 28 Mar 2017 15:15 |
| Last Modified: | 09 Aug 2023 12:41 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/18360 |
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