Context-Aware Semantic Association Ranking

TitleContext-Aware Semantic Association Ranking
Publication TypeConference Paper
Year of Publication2003
AuthorsBoanerges Aleman-Meza, Chris Halaschek, Ismailcem Budak Arpinar, Amit Sheth
Conference Name1st International Conference on Semantic Web and Databases (SWDB 2003)
Date Published09/2003
Conference LocationBerlin, Germany

Discovering complex and meaningful relationships, which we call Semantic Associations, is an important challenge. Just as ranking of documents is a critical component of today's search engines, ranking of relationships will be essential in tomorrow's semantic search engines that would support discovery and mining of the Semantic Web. Building upon our recent work on specifying types of Semantic Associations in RDF graphs, which are possible to create through semantic metadata extraction and annotation, we discuss a framework where ranking techniques can be used to identify more interesting and more relevant Semantic Associations. Our techniques utilize alternative ways of specifying the context using ontology. This enables capturing users' interests more precisely and better quality results in relevance ranking.

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