SSERank: semantic search engine for page ranking based on the relations weight. (12th April 2010) - Slimani, Thabet
Semantic search engines promise to provide more accurate results than current keywords search engines. However, it is useful to exploit ontological relations in search steps. In this paper, we present an approach which automatically exploits the keywords in a user query to find related concepts in domain ontology. Given an ontology and some annotated pages, the weights assigned to relations in a given page indicate its strength. However, in order to rank results, we assign a weight for each annotated page. This paper proposes a prototype (SSERank) relation-based page weighting and ranking with semantic search capability. The obtained results show that SSERank will have great utility although there is potential for improvement.