Constructing Feature Vectors for search: investigating intrinsic quality impact on search performance

  • Authors:
  • Stein L. Tomassen;Darijus Strasunskas

  • Affiliations:
  • Department of Computer and Information Science, Norwegian University of Science and Technology, NO-7491 Trondheim, Norway.;Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology, NO-7491 Trondheim, Norway

  • Venue:
  • International Journal of Web and Grid Services
  • Year:
  • 2010

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Abstract

In this paper, we revisit our approach to construction of semantic-linguistic Feature Vectors (FVs) used to enhance Web search. These FVs are built based on domain semantics encoded in an ontology and augmented by relevant terminology from Web documents. The contributions of this paper are the evaluation of constructed FVs and the analysis of their impact on search performance. This completes the validation of the proposed approach concluding that the proposed metrics provide good indications of the quality of the FVs. Yet, the results suggest that the metrics need to be tailored to fit the needs of search applications.