The full text of this article


Measuring intrinsic quality of semantic search based on feature vectors
by Stein L. Tomassen, Darijus Strasunskas
International Journal of Metadata, Semantics and Ontologies (IJMSO), Vol. 5, No. 2, 2010


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.

Online publication date: Sun, 16-May-2010


is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Metadata, Semantics and Ontologies (IJMSO):
Login with your Inderscience username and password:


    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email