Document Type
Conference Proceeding
Publication Date
2004
Abstract
Information retrieval over semantic metadata has recently received a great amount of interest in both industry and academia. In particular, discovering complex and meaningful relationships among this data is becoming an active research topic. Just as ranking of documents is a critical component of today's search engines, the ranking of relationships will be essential in tomorrow's semantic analytics engines. Building upon our recent work on specifying these semantic relationships, which we refer to as Semantic Associations, we demonstrate a system where these associations are discovered among a large semantic metabase represented in RDF. Additionally we employ ranking techniques to provide users with the most interesting and relevant results.
Repository Citation
Halaschek-Wiener, C.,
Aleman-Meza, B.,
Arpinar, I. B.,
& Sheth, A. P.
(2004). Discovering and Ranking Semantic Associations over a Large RDF Metabase. Proceedings of the Thirtieth International Conference on Very Large Data Bases, 1317-1320.
https://corescholar.libraries.wright.edu/knoesis/734
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 Thirtieth International Conference on Very Large Data Bases, Toronto, Canada, August 31-September 3, 2004.