Document Type
Presentation
Publication Date
9-2013
Abstract
Linked Open Data (LOD) cloud has gained significant attention in the Semantic Web community recently. Currently it consists of approximately 295 interlinked datasets with over 50 billion triples including 500 million links, and continues to expand in size. This vast source of structured information has the potential to have a significant impact on knowledge-based applications. However, a key impediment to the use of LOD cloud is limited support for data integration tasks over concepts, instances, and properties. Efforts to address this limitation over properties have focused on matching data-type properties across datasets; however, matching of object-type properties has not received similar attention. We present an approach that can automatically match object-type properties across linked datasets, primarily exploiting and bootstrapping from entity co-reference links such as owl:sameAs. Our evaluation, using sample instance sets taken from Freebase, DBpedia, LinkedMDB, and DBLP datasets covering multiple domains shows that our approach matches properties with high precision and recall (on average, F measure gain of 57% - 78%).
Repository Citation
Gunaratna, K.,
Thirunarayan, K.,
Jain, P.,
Sheth, A. P.,
& Wijeratne, S.
(2013). A Statistical and Schema Independent Approach to Identify Equivalent Properties on Linked Data. .
https://corescholar.libraries.wright.edu/knoesis/565
DOI
10.1145/2506182.2506187
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 9th International Conference on Semantic Systems (I-Semantics), Messe Graz, Austria, September 4th-6th, 2013.
Paper that accompanied the presentation can be found at http:dx.doi.org/10.1145/2506182.2506187.