Details
Originalsprache | Englisch |
---|---|
Titel des Sammelwerks | WoLE 2012 Web of Linked Entities |
Untertitel | Proceedings of the Web of Linked Entities Workshop in conjuction with the 11th International Semantic Web Conference (ISWC 2012) |
Seiten | 45-57 |
Seitenumfang | 13 |
Publikationsstatus | Veröffentlicht - 21 Sept. 2012 |
Veranstaltung | Web of Linked Entities, WoLE 2012 - Workshop in Conjunction with the 11th International Semantic Web Conference, ISWC 2012 - Boston, MA, USA / Vereinigte Staaten Dauer: 11 Nov. 2012 → 11 Nov. 2012 |
Publikationsreihe
Name | CEUR Workshop Proceedings |
---|---|
Herausgeber (Verlag) | CEUR Workshop Proceedings |
Band | 906 |
ISSN (Print) | 1613-0073 |
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 ofWeb 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 correlatedWeb resources. Finally, we present an evaluation of our approach using the publicly available datasets Bibsonomy and USAToday.
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WoLE 2012 Web of Linked Entities: Proceedings of the Web of Linked Entities Workshop in conjuction with the 11th International Semantic Web Conference (ISWC 2012) . 2012. S. 45-57 (CEUR Workshop Proceedings; Band 906).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Can Entities be Friends?
AU - Nunes, Bernardo Pereira
AU - Kawase, Ricardo
AU - Dietze, Stefan
AU - Taibi, Davide
AU - Casanova, Marco Antonio
AU - Nejdl, Wolfgang
PY - 2012/9/21
Y1 - 2012/9/21
N2 - 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 ofWeb 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 correlatedWeb resources. Finally, we present an evaluation of our approach using the publicly available datasets Bibsonomy and USAToday.
AB - 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 ofWeb 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 correlatedWeb resources. Finally, we present an evaluation of our approach using the publicly available datasets Bibsonomy and USAToday.
KW - Data integration
KW - Link detection
KW - Linked data
KW - Semantic associations
UR - http://www.scopus.com/inward/record.url?scp=84891929625&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84891929625
T3 - CEUR Workshop Proceedings
SP - 45
EP - 57
BT - WoLE 2012 Web of Linked Entities
T2 - Web of Linked Entities, WoLE 2012 - Workshop in Conjunction with the 11th International Semantic Web Conference, ISWC 2012
Y2 - 11 November 2012 through 11 November 2012
ER -