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Peer-to-Peer Information Search: Semantic, Social, or Spiritual?

MPG-Autoren
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;

Kacimi,  Mouna
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/persons45166

Parreira,  Josiane Xavier
Databases and Information Systems, 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

Bender, M., Crecelius, T., Kacimi, M., Michel, S., Parreira, J. X., & Weikum, G. (2007). Peer-to-Peer Information Search: Semantic, Social, or Spiritual? Bulletin of the Technical Committee on Data Engineering, 30(2), 51-60.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000F-204A-A
Zusammenfassung
We consider the network structure and query processing capabilities of social communities like bookmarks and photo sharing communities such as del.icio.us or flickr. A common feature of all these networks is that the content is generated by the users and that users create social links with other users. The evolving network naturally resembles a peer-to-peer system, where the peers correspond to users. We consider the problem of query routing in such a peer-to-peer setting where peers are collaborating to form a distributed search engine. We have identified three query routing paradigms: semantic routing based on query-to-content similarities, social routing based on friendship links within the community, and spiritual routing based on user-to-user similarities such as shared interests or similar behavior. We discuss how these techniques can be integrated into an existing peer-to-peer search engine and present a performance study on search-result quality using real-world data obtained from the social bookmark community del.icio.us.