Measuring intrinsic quality of semantic search based on feature vectors

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 Metadata, Semantics and Ontologies
Year:
2010

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Abstract

Search is probably the most frequent activity on the web. Yet, it is not effortless, mainly due to heterogeneous information resources. Semantic search is a means to tackle the problem of ambiguity. In this paper, we analyse a process of constructing semantic-linguistic Feature Vectors (FVs) used in our semantic search approach. These FVs are built based on domain semantics encoded in an ontology and enhanced by relevant terminology from web documents. Since FVs are central building blocks of the approach, we investigate the quality of FVs. We take a closer look at the process of FV construction and the impact of chosen techniques on the quality of FVs. We report on a set of laboratory experiments and analyse aspects affecting the FV quality and the FV construction error rates.