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P2P Authority Analysis for Social Communities

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons45166

Parreira,  Josiane Xavier
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45041

Michel,  Sebastian
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44113

Bender,  Matthias
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44267

Crecelius,  Tom
Databases and Information Systems, MPI for Informatics, Max Planck Society;
International Max Planck Research School, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45720

Weikum,  Gerhard
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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Zitation

Parreira, J. X., Michel, S., Bender, M., Crecelius, T., & Weikum, G. (2007). P2P Authority Analysis for Social Communities. In C. Koch, J. Gehrke, M. Garofalakis, D. Srivastava, K. Aberer, A. Deshpande, et al. (Eds.), 33rd International Conference on Very Large Data Bases (VLDB 2007) (pp. 1398-1401). New York, NY, USA: ACM.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000F-203C-C
Zusammenfassung
Page{R}ank-style authority analyses of Web graphs are of great importance for {W}eb mining. Such authority analyses also apply to hot ``Web 2.0'' applications that exhibit a natural graph structure, such as social networks (e.g., My{S}pace, {F}acebook) or tagging communities (e.g., Flickr, Del.icio.us). Finding the most trustworthy or most important authorities in such a community is a pressing need, given the huge scale and also the anonymity of social networks. Computing global authority measures in a Peer-to-Peer ({P2P}) collaboration of autonomous peers is a hot research topic, in particular because of the incomplete local knowledge of the peers, which typically only know about (arbitrarily overlapping) sub-graphs of the complete graph. We demonstrate a self-organizing {P2P} collaboration that, based on the local sub-graphs, efficiently computes global authority scores. In hand with the loosely-coupled spirit of a {P2P} system, the computation is carried out in a completely asynchronous manner without any central knowledge or coordinating instance. We demonstrate the applicability of authority analyses to large-scale distributed systems.