A DISTRIBUTED INFORMATION FILTERING: STAKES AND SOLUTION FOR SATELLITE BROADCASTING

Sylvain Castagnos, Anne Boyer, François Charpillet

Abstract

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 et al., 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.

References

  1. Breese, J. S., Heckerman, D., and Kadie, C. (1998). Empirical analysis of predictive algorithms for collaborative filtering. In Proceedings of the fourteenth Annual Conference on Uncertainty in Artificial Intelligence (UAI-98), pages 43-52, San Francisco, CA.
  2. Chan, P. (1999). A non-invasive learning approach to building web user profiles. In Workshop on Web usage analysis and user profiling, Fifth International Conference on Knowledge Discovery and Data Mining, San Diego.
  3. Chee, S. H. S., Han, J., and Wang, K. (2001). Rectree : An efficient collaborative filtering method'. In Proceedings 2001 Int. Conf. on Data Warehouse and Knowledge Discovery (DaWaK'01), Munich, Germany.
  4. Goldberg, K., Roeder, T., Huptan, D., and Perkins, C. (2000). Eigentaste : a constant time collaborative filtering algorithm. Technical Report M00/41, IEOR and EECS Departments, UC Berkeley.
  5. Herlocker, J. L., Konstant, J. A., Borchers, A., and Riedl, J. (1999). An algorithmic framework for performing collaborative filtering. In In Proceedings 1999 Conference of Research and Development in Information Retrieval, pages pages 230-237, Berkeley, CA.
  6. Kassab, R., Lamirel, J.-C., and Nauer, E. (2005). Novelty detection for modeling user's profile. In International Conference FLAIRS 2005, Clearwater Beach, Florida, USA.
  7. Resnick, P., Iacovou, N., Suchak, M., Bergstorm, P., and Riedl, J. (1994). Grouplens: An open architecture for collaborative filtering of netnews. In Proceedings of ACM 1994 Conference on Computer Supported Cooperative Work, pages 175-186, Chapel Hill, North Carolina. ACM.
  8. Sarwar, B. M., Karypis, G., Konstan, J. A., and Reidl, J. (2001). Item-based collaborative filtering recommendation algorithms. In World Wide Web, pages 285- 295.
  9. Shardanand, U. and Maes, P. (1995). Social information filtering: Algorithms for automating “word of mouth”. In Proceedings of ACM CHI'95 Conference on Human Factors in Computing Systems, volume 1, pages 210-217.
  10. Ungar, L. and Foster, D. (1998). Clustering methods for collaborative filtering. In Proceedings of the Workshop on Recommendation Systems, Menlo Park California. AAAI Press.
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Paper Citation


in Harvard Style

Castagnos S., Boyer A. and Charpillet F. (2005). A DISTRIBUTED INFORMATION FILTERING: STAKES AND SOLUTION FOR SATELLITE BROADCASTING . In Proceedings of the First International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, ISBN 972-8865-20-1, pages 299-304. DOI: 10.5220/0001231302990304


in Bibtex Style

@conference{webist05,
author={Sylvain Castagnos and Anne Boyer and François Charpillet},
title={A DISTRIBUTED INFORMATION FILTERING: STAKES AND SOLUTION FOR SATELLITE BROADCASTING},
booktitle={Proceedings of the First International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,},
year={2005},
pages={299-304},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001231302990304},
isbn={972-8865-20-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
TI - A DISTRIBUTED INFORMATION FILTERING: STAKES AND SOLUTION FOR SATELLITE BROADCASTING
SN - 972-8865-20-1
AU - Castagnos S.
AU - Boyer A.
AU - Charpillet F.
PY - 2005
SP - 299
EP - 304
DO - 10.5220/0001231302990304