RoSeS: a continuous query processor for large-scale RSS filtering and aggregation

Authors:
Jordi Creus;Bernd Amann;Nicolas Travers;Dan Vodislav
Affiliations:
Université Pierre et Marie Curie, Paris, France;Université Pierre et Marie Curie, Paris, France;Conservatoire National des Arts et Métiers, Paris, France;Université de Cergy-Pontoise, Cergy-Pontoise, France
Venue:
Proceedings of the 20th ACM international conference on Information and knowledge management
Year:
2011

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Abstract

We present RoSeS, a running system for large-scale content-based RSS feed filtering and aggregation. The implementation of RoSeS is based on standard database concepts like declarative query languages, views and multi-query optimization. Users create personalized feeds by defining and composing content-based filtering and aggregation queries on collections of RSS feeds. These queries are translated into continuous multi-query execution plans which are optimized using a new cost-based multi-query optimization strategy.