Peer-Sensitive objectrank – valuing contextual information in social networks

Authors:
Andrei Damian;Wolfgang Nejdl;Raluca Paiu
Affiliations:
L3S Research Center / University of Hanover, Hanover, Germany;L3S Research Center / University of Hanover, Hanover, Germany;L3S Research Center / University of Hanover, Hanover, Germany
Venue:
WISE'05 Proceedings of the 6th international conference on Web Information Systems Engineering
Year:
2005

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Abstract

Building on previous work on how to model contextual information for desktop search and how to implement semantically rich information exchange in social networks, we define a new algorithm, Peer-Sensitive ObjectRank for ranking resources on the desktop. The new algorithm takes into account different trust values for each peer, generalizing previous biasing PageRank algorithms. We investigate in detail, how different assumptions about trust distributions influence the ranking of information received from different peers, and which consequences they have with respect to integration of new resources into one peer’s initial network of resources. We also investigate how assumptions concerning size and quality of a peer’s resource network influence ranking after information exchange, and conclude with directions for further research.