Hybrid search: effectively combining keywords and semantic searches

  • Authors:

  • Ravish Bhagdev;Sam Chapman;Fabio Ciravegna;Vitaveska Lanfranchi;Daniela Petrelli

  • Affiliations:

  • Department of Computer Science, University of Sheffield, Sheffield, United Kingdom;Department of Computer Science, University of Sheffield, Sheffield, United Kingdom;Department of Computer Science, University of Sheffield, Sheffield, United Kingdom;Department of Computer Science, University of Sheffield, Sheffield, United Kingdom;Department of Information Studies, University of Sheffield, Sheffield, United Kingdom

  • Venue:
  • ESWC'08 Proceedings of the 5th European semantic web conference on The semantic web: research and applications
  • Year:
  • 2008

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Abstract

This paper describes hybrid search, a search method supporting both document and knowledge retrieval via the flexible combination of ontology-based search and keyword-based matching. Hybrid search smoothly copes with lack of semantic coverage of document content, which is one of the main limitations of current semantic search methods. In this paper we define hybrid search formally, discuss its compatibility with the current semantic trends and present a reference implementation: K-Search. We then show how the method outperforms both keyword-based search and pure semantic search in terms of precision and recall in a set of experiments performed on a collection of about 18.000 technical documents. Experiments carried out with professional users show that users understand the paradigm and consider it very powerful and reliable. K-Search has been ported to two applications released at Rolls-Royce plc for searching technical documentation about jet engines.