Issue No. 01 - January (2009 vol. 21)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TKDE.2008.113
Fabrizio Lamberti , Politecnico di Torino, Torino
Andrea Sanna , Politecnico di Torino, Torino
Claudio Demartini , Politecnico di Torino, Torino
With the tremendous growth of information available to end users through the Web, search engines come to play ever a more critical role. Nevertheless, because of their general purpose approach, it is always less uncommon that obtained result sets provide a burden of useless pages. Next generation Web architecture, represented by Semantic Web, provides the layered architecture possibly allowing to overcome this limitation. Several search engines have been proposed, which allow to increase information retrieval accuracy by exploiting a key content of Semantic Web resources, that is relations. However, in order to rank results, most of the existing solutions need to work on the whole annotated knowledge base. In this paper we propose a relation-based page rank algorithm to be used in conjunction with Semantic Web search engines that simply relies on information which could be extracted from user query and annotated resource. Relevance is measured as the probability that retrieved resource actually contains those relations whose existence was assumed by the user at the time of query definition.
Intelligent Web Services and Semantic Web, Knowledge retrieval, Search process, Query formulation
F. Lamberti, A. Sanna and C. Demartini, "A Relation-Based Page Rank Algorithm for Semantic Web Search Engines," in IEEE Transactions on Knowledge & Data Engineering, vol. 21, no. , pp. 123-136, 2008.