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[HdT15a] TDV-based Filter for Novelty and Diversity in a Real-time Pub/Sub System

Conférence Internationale avec comité de lecture : IDEAS'15, International Database Engineering & Applications Symposium, July 2015, Vol. 19, pp.136--145, Yokohama, Japon, (DOI: 10.1145/2790755.2790768)

Mots clés: Pub/Sub, Novelty & Diversity, Web Syndication, TDV

Résumé: Publish/Subscribe (Pub/Sub) systems have been designed to face the exponential growth of information published on the Web by subscribing to sources of interest which produce flows of items. However users may receive some information several times, or information that does not contain any new content, and conversely miss some information of interest hidden in all information received. Pub/Sub systems are consequently witnessing a real challenge to efficiently filter relevant information. We propose in this paper a scalable approach for filtering news (items) which match the user interests (expressed as subscriptions). Introducing for the first time TDV (Term Discrimination Value) in this context, which allows to measure how a term discrimines an item, we filter out in real-time items whose content has al- ready been notified recently to the user, either in another item (filtering by novelty) or globally in his recent history (filtering by diversity). Our experiments illustrate the impact of our different parameters and confirm the scalability of our approach and the relevance of the results notified.

Equipe: isid , vertigo

BibTeX

@inproceedings {
HdT15a,
title="{TDV-based Filter for Novelty and Diversity in a Real-time Pub/Sub System}",
author=" Z. Hmedeh and C. du Mouza and N. Travers ",
booktitle="{IDEAS'15, International Database Engineering & Applications Symposium}",
year=2015,
month="July",
volume=19,
pages="136--145",
address="Yokohama, Japon",
doi="10.1145/2790755.2790768",
}