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Efficient Search and Approximate Information Filtering in a Distributed Peer-to-Peer Environment of Digital Libraries

MPG-Autoren
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/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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Zitation

Zimmer, C., Tryfonopoulos, C., & Weikum, G. (2007). Efficient Search and Approximate Information Filtering in a Distributed Peer-to-Peer Environment of Digital Libraries. In C. Thanos, F. Borri, & L. Candela (Eds.), Digital Libraries: Research and Development, First International DELOS Conference (pp. 328-337). Berlin, Germany: Springer.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000F-1F01-4
Zusammenfassung
We present a new architecture for efficient search and approximate information filtering in a distributed {P}eer-to-{P}eer ({P2P}) environment of Digital Libraries. The {M}inerva{L}ight search system uses {P2P} techniques over a structured overlay network to distribute and maintain a directory of peer statistics. Based on the same directory, the {MAPS} information filtering system provides an approximate publish/subscribe functionality by monitoring the most promising digital libraries for publishing appropriate documents regarding a continuous query. In this paper, we discuss our system architecture that combines searching and information filtering abilities. We show the system components of {M}inerva{L}ight and explain the different facets of an approximate pub/sub system for subscriptions that is high scalable, efficient, and notifies the subscribers about the most interesting publications in the {P2P} network of digital libraries. We also compare both approaches in terms of common properties and differences to show an overview of search and pub/sub using the same infrastructure.