Document Type
Conference Proceeding
Publication Date
9-2003
Abstract
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.
Repository Citation
Aleman-Meza, B.,
Halaschek-Wiener, C.,
Arpinar, I. B.,
& Sheth, A. P.
(2003). Context-Aware Semantic Association Ranking. .
https://corescholar.libraries.wright.edu/knoesis/729
Included in
Bioinformatics Commons, Communication Technology and New Media Commons, Databases and Information Systems Commons, OS and Networks Commons, Science and Technology Studies Commons
Comments
Presented at the 1st International Workshop on Semantic Web and Databases, Berlin, Germany, September 7-8, 2003.