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Conference Paper

P2P Information Retrieval and Filtering with MAPS (Demo)

MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons45808

Zimmer,  Christian
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44604

Heinz,  Johannes
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45639

Tryfonopoulos,  Christos
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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Citation

Zimmer, C., Heinz, J., Tryfonopoulos, C., & Weikum, G. (2008). P2P Information Retrieval and Filtering with MAPS (Demo). In K. Wehrle, W. Kellerer, S. K. Singhal, & R. Steinmetz (Eds.), P2P’08: Eighth International Conference on Peer-to-Peer Computing (pp. 84-85). Washington, DC: IEEE Computer Society.


Cite as: http://hdl.handle.net/11858/00-001M-0000-000F-1C93-5
Abstract
In this demonstration paper we present MAPS, a novel system that combines approximate information retrieval and filtering functionality in a peer-to-peer setting. In MAPS, a user is able to submit one-time and continuous queries, and receive matching resources and notifications from selected information sources. The selection of these sources in the retrieval case is based on well-known resource selection techniques for peer-to-peer query routing, while in the filtering case a combination of resource selection and novel behavior prediction techniques using time-series analysis of publisher statistics is used. The integration of the two functionalities is done in a seamless way utilizing the same machinery: a conceptually global, but physically distributed directory of statistics about information sources based on distributed hash tables.