FiND: a real-time filtering by novelty and diversity for publish/subscribe systems

Abstract

Content syndication has become a popular way for timely delivery of frequently updated information on the Web. It essentially enhances traditional pull-oriented searching and browsing of web pages with push-oriented protocols. However many Web syndication applications imply a tight coupling between feed producers and consumers and do not help users to find, in all information they received, items with interesting and new content. We present the FiND Pub/Sub system which integrates an in-memory filtering process based on keyword subscriptions. Unlike existing proposals, FiND is designed for real-time notifications on item streams. This demonstration illustrates the main features of the FiND system namely (i) a scalable real-time notification process when the most important terms of the subscription are matched, (ii) a tunable filtering by novelty and diversity to reduce user flooding.