G-ToPSS: fast filtering of graph-based metadata

  • Authors:
  • Milenko Petrovic;Haifeng Liu;Hans-Arno Jacobsen

  • Affiliations:
  • University of Toronto, Toronto, ON, Canada;University of Toronto, Toronto, ON, Canada;University of Toronto, Toronto, ON, Canada

  • Venue:
  • WWW '05 Proceedings of the 14th international conference on World Wide Web
  • Year:
  • 2005

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Abstract

RDF is increasingly being used to represent metadata. RDF Site Summary (RSS) is an application of RDF on the Web that has considerably grown in popularity. However, the way RSS systems operate today does not scale well. In this paper we introduce G-ToPSS, a scalable publish/subscribe system for selective information dissemination. G-ToPSS is particularly well suited for applications that deal with large-volume content distribution from diverse sources. RSS is an instance of the content distribution problem. G-ToPSS allows use of ontology as a way to provide additional information about the data. Furthermore, in this paper we show how G-ToPSS can support RDFS class taxonomies. We have implemented and experimentally evaluated G-ToPSS and we provide results in the paper demonstrating its scalability compared to alternatives.