Lopes, G.R.; Leme, L.A.P.P.; Pereira Nunes, B.; Casanova, M.A.; Dietze, S.: Recommending tripleset interlinking through a social network approach. In: Lin, X.; Manolopoulos, Y.; Srivastava, D.; Huang, G. (Eds.): Web Information Systems Engineering – WISE 2013. Heidelberg : Springer Verlag (Lecture Notes in Computer Science ; 8180), S. 149-161. DOI:
https://doi.org/10.1007/978-3-642-41230-1_13
Zusammenfassung: |
Tripleset interlinking is one of the main principles of Linked Data. However, the discovery of existing triplesets relevant to be linked with a new tripleset is a non-trivial task in the publishing process. Without prior knowledge about the entire Web of Data, a data publisher must perform an exploratory search, which demands substantial effort and may become impracticable, with the growth and dissemination of Linked Data. Aiming at alleviating this problem, this paper proposes a recommendation approach for this scenario, using a Social Network perspective. The experimental results show that the proposed approach obtains high levels of recall and reduces in up to 90% the number of triplesets to be further inspected for establishing appropriate links. The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-41230-1_13.
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Lizenzbestimmungen: |
Es gilt deutsches Urheberrecht. Das Dokument darf zum eigenen Gebrauch kostenfrei genutzt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden. |
Publikationstyp: |
BookPart |
Publikationsstatus: |
acceptedVersion |
Erstveröffentlichung: |
2013 |
Schlagwörter (englisch): |
Linked Data, Recommender Systems, Social Networks, Exploratory search, Linked datum, Non-trivial tasks, Prior knowledge, Publishing process, Web of datum, Data handling, Systems engineering, World Wide Web
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Fachliche Zuordnung (DDC): |
004 | Informatik
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Kontrollierte Schlagwörter: |
Konferenzschrift
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