The richness of the (Semantic) Web lies in its ability to link related resources as well as data across the Web. However, while relations within particular datasets are often well defined, links between disparate datasets and corpora of Web resources are rare. The increasingly widespread use of cross-domain reference datasets, such as Freebase and DBpedia for annotating and enriching datasets as well as document corpora, opens up opportunities to exploit their inherent semantics to uncover semantic relationships between disparate resources. In this paper, we present an approach to uncover relationships between disparate entities by analyzing the graphs of used reference datasets. We adapt a relationship assessment methodology from social network theory to measure the connectivity between entities in reference datasets and exploit these measures to identify correlated Web resources. Finally, we present an evaluation of our approach using the publicly available datasets Bibsonomy and USAToday.

@inproceedings{pereiranunes2012entities, author = {Pereira Nunes, Bernardo and Kawase, Ricardo and Dietze, Stefan and Taibi, Davide and Casanova, Marco Antonio and Nejdl, Wolfgang}, title = {Can Entities be Friends?}, editor = {Rizzo, Giuseppe and Mendes, Pablo and Charton, Eric and Hellmann, Sebastian and Kalyanpur, Aditya}, booktitle = {Proceedings of the Web of Linked Entities Workshop in conjuction with the 11th International Semantic Web Conference}, series = {CEUR-WS.org}, year = {2012}, volume = {906}, pages = {45--57}, url = {http://ceur-ws.org/Vol-906/paper6.pdf}, keywords = {data, detection, entity, graph, linked, relation, web}, abstract = {The richness of the (Semantic) Web lies in its ability to link related resources as well as data across the Web. However, while relations within particular datasets are often well defined, links between disparate datasets and corpora of Web resources are rare. The increasingly widespread use of cross-domain reference datasets, such as Freebase and DBpedia for annotating and enriching datasets as well as document corpora, opens up opportunities to exploit their inherent semantics to uncover semantic relationships between disparate resources. In this paper, we present an approach to uncover relationships between disparate entities by analyzing the graphs of used reference datasets. We adapt a relationship assessment methodology from social network theory to measure the connectivity between entities in reference datasets and exploit these measures to identify correlated Web resources. Finally, we present an evaluation of our approach using the publicly available datasets Bibsonomy and USAToday. } }

%0 = inproceedings %A = Pereira Nunes, Bernardo and Kawase, Ricardo and Dietze, Stefan and Taibi, Davide and Casanova, Marco Antonio and Nejdl, Wolfgang %B = Proceedings of the Web of Linked Entities Workshop in conjuction with the 11th International Semantic Web Conference %D = 2012 %T = Can Entities be Friends? %U = http://ceur-ws.org/Vol-906/paper6.pdf