Result: A Distributed Information Filtering: Stakes and solution for satellite broadcasting

Title:
A Distributed Information Filtering: Stakes and solution for satellite broadcasting
Contributors:
Autonomous intelligent machine (MAIA), INRIA Lorraine, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS), Institute for Systems and Technologies of Information, Control and Communication (INSTICC), José Cordeiro, Vitor Pedrosa, Bruno Encarnação, Joaquim Filipe
Source:
First International Conference on Web Information Systems and Technologies (WEBIST'05). :299-304
Publisher Information:
CCSD; INSTICC Press, 2005.
Publication Year:
2005
Collection:
collection:CNRS
collection:INRIA
collection:INPL
collection:INRIA-LORRAINE
collection:LORIA2
collection:INRIA-NANCY-GRAND-EST
collection:TESTALAIN1
collection:UNIV-LORRAINE
collection:INRIA2
collection:LORIA
collection:INRIA-300009
collection:AM2I-UL
Original Identifier:
HAL:
Document Type:
Conference conferenceObject<br />Conference papers
Language:
English
Rights:
info:eu-repo/semantics/OpenAccess
Accession Number:
edshal.inria.00000508v1
Database:
HAL

Further Information

This paper is a preliminary report which presents information filtering solutions designed within the scope of a collaboration between our laboratory and the company of broadcasting per satellite SES ASTRA. The latter have finalized a system sponsored by advertisement and supplying to users a high bandwidth access to hundreds of web sites for free. This project aims at highlighting the benefits of collaborative filtering by including such a module in the architecture of their product. The term of collaborative filtering [Goldberg, 2000] denotes techniques using the known preferences of a group of users to predict the unknown preference of a new user. Our problem has consisted in finding a way to provide scale for hundreds thousands of people, while preserving anonymity of users (personal data remain on client side). Thus, we use an existing clustering method, that we have improved so that it is distributed respectively on client and server side. Nevertheless, in the absence of numerical votes for marketing reasons, we have chosen to do an innovative combination of this decentralized collaborative filtering method with a user profiling technique. We have also been submitted to constraints such as a short answer time on client side, in order to be compliant with the ASTRA architecture.