Trust-based Recommendations in Multi-layer Networks

Autor/en:
C. Heß
Umfang:
216
EAN/ISBN:
978-3-89838-316-5
Erscheinungsdatum:
Montag, 30. Juni 2008
Band:
316
Ausgabe:
softcover
Buchreihe:
Dissertationen zur Künstlichen Intelligenz
Kategorien:
Buch
Informatik
Künstliche Intelligenz
Allgemeine Computer- und Kommunikationswissenschaft
Dissertationen zur Künstlichen Intelligenz
Englisch
Gesamtverzeichnis AKA Verlag#Complete Index AKA Publisher
Preis:
inkl. 7% MWSt
50,00 €
The huge interest in social networking applications – Friendster.com, for example, has more than 40 million users – led to a considerable research interest in using this data for generating recommendations. Especially recommendation techniques that analyze trust networks were found to provide very accurate and highly personalized results. The main contribution of this work is to extend the approach to trust-based recommendations, which up to now have been made for isolated items such as movies, to linked resources, in particular documents. Therefore, a second type of network, namely a document reference network, is considered apart from the trust network. This is, for example, the citation network of scientific publications. Recommendations for documents are typically made by reference-base visibility measures which consider a document to be the more important, the more often it is referenced by important documents. Document and trust networks, as well as further networks such as organization networks are integrated in a multi-layer network. This architecture allows for combining classical visibility measures with trust-based recommendations, giving trust-enhanced visibility measures. The trust-based recommender system for scientific publications SPRec implements a two-layer architecture and provides personalized recommendations via a web interface.