Measuring intrinsic quality of semantic search based on feature vectors

: 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 (FV) 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.

• Type: Journal
• Year: 2010
• Where: IJMSO
• Authors: Stein L. Tomassen, Darijus Strasunskas
• Keywords: FV Construction, FV Construction Error, IJMSO 2010, Semantic Search