Ranking semantic relationships between two entities using personalization in context specification
Semantic relationship deals with complex relationship between two entities in a knowledge base. In the process of finding the relationship, multiple paths connecting entities could be explored. Each path has a different meaning depending on the type of relation. Some of them may be relevant while others may be irrelevant depending on users perspective with varying results for the same query. Hence, ranking these paths according to the users need is imperative. In this paper, we adopt personalization approach to rank the semantic relationship paths. Here, users interest level in various domains can be captured through their web browsing history and it is incorporated in calculating the context weights of the paths during the ranking process. The effectiveness of the ranking method is demonstrated through Spearmans foot rule correlation and precision rate. The experimental results prove that our proposed method is more efficient for ranking semantic relationship paths.
personalization semantic web semantic association semantic web usage context rdf rdf schema