SSERank: semantic search engine for page ranking based on the relations weight. (12th April 2010)

• Record Type: Journal Article
• Authors: Slimani, Thabet; Yaghlane, Boutheina Ben; Mellouli, Khaled
• Is Part Of: International journal of metadata, semantics and ontologies. Volume 5:Number 1(2010)
• Page Start: 72
• Page End: 84
• Publication Date: 2010-04-12
• Subjects: semantic web -- semantic search -- relation weight -- page ranking -- ontological relations -- ontology -- semantic association -- knowledge retrieval -- metadata -- search engines -- page weighting; Metadata -- Periodicals; Semantic Web -- Periodicals; Ontologies (Information retrieval) -- Periodicals; Data structures (Computer science) -- Periodicals; Information theory -- Periodicals; 005.74
• Languages: English
• ISSNs: 1744-2621

Abstract

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.