Entity-based Semantic Association Ranking on the Semantic Web
S. Narayana, S. Sivaleela, Aliseri Govardhan, G. P. Saradhi Varma · International Journal of Computer Applications · 2013
The major focus of today's search engines is efficient retrieval of relevant documents from the web.Recently Semantic Web has received greater interest in industry and academia and retrieving relevant information over huge amounts of Semantic Meta data is becoming popular.In particular discovering and ranking complex relationships between two entities over Semantic Meta data became a challenging research topic.Semantic Associations capture complex relationships between two entities in an RDF knowledge base.Given two entities, there exist a huge number of Semantic Associations between entities.Moreover these associations pass through one more intermediate entity.Hence ranking of associations is required in order to get relevant associations.This paper proposes an approach to discover and rank Semantic Associations between two entities based on the user interest.User interest is captured by selecting one or more entities from the user interface.The effectiveness of the ranking method is demonstrated using Spearman Foot rule coefficient.The results show that the proposed ranking is highly correlated with human ranking.