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Title: Ontology-based faceted semantic search with automatic sense disambiguation for bioenergy domain

Authors: Feroz Farazi; Craig Chapman; Pathmeswaran Raju; Lynsey Melville

Addresses: Knowledge Based Engineering (KBE) Lab, Faculty of Computing, Engineering and the Built Environment, Birmingham City University, City Centre Campus, Millennium Point, Birmingham, B4 7XG, UK ' Knowledge Based Engineering (KBE) Lab, Faculty of Computing, Engineering and the Built Environment, Birmingham City University, City Centre Campus, Millennium Point, Birmingham, B4 7XG, UK ' Knowledge Based Engineering (KBE) Lab, Faculty of Computing, Engineering and the Built Environment, Birmingham City University, City Centre Campus, Millennium Point, Birmingham, B4 7XG, UK ' Centre for Low Carbon Research, Faculty of Computing, Engineering and the Built Environment, Birmingham City University, City Centre Campus, Millennium Point, Birmingham, B4 7XG, UK

Abstract: WordNet is a lexicon widely known and used as an ontological resource hosting comparatively large collection of semantically interconnected words. Use of such resources produces meaningful results and improves users' search experience through the increased precision and recall. This paper presents our facet-enabled WordNet powered semantic search work done in the context of the bioenergy domain. The main hurdle to achieving the expected result was sense disambiguation further complicated by the occasional fine-grained distinction of meanings of the terms in WordNet. To overcome this issue, this paper proposes a sense disambiguation methodology that uses bioenergy domain related ontologies (extracted from WordNet automatically), WordNet concept hierarchy and term sense rank.

Keywords: semantic search; faceted search; faceted semantic search; knowledge base; WordNet; ontology; bioenergy; semantics; domain; domain ontologies.

DOI: 10.1504/IJBDI.2018.088286

International Journal of Big Data Intelligence, 2018 Vol.5 No.1/2, pp.62 - 72

Available online: 29 Sep 2017 *

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