A multi-system analysis of document and term selection for blind feedback

  • Authors:
  • Thomas R. Lynam;Chris Buckley;Charles L. A. Clarke;Gordon V. Cormack

  • Affiliations:
  • University of Waterloo, Canada;Sabir Research Inc., Gaithersburg, MD;University of Waterloo, Canada;University of Waterloo, Canada

  • Venue:
  • Proceedings of the thirteenth ACM international conference on Information and knowledge management
  • Year:
  • 2004

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Abstract

Experiments were conducted to explore the impact of combining various components of eight leading information retrieval systems. Each system demonstrated improved effectiveness with the use of blind feedback, in which the results of a preliminary retrieval step were used to augment the efficacy of a secondary retrieval step. The hybrid combination of primary and secondary retrieval steps from different systems in a number of cases yielded better effectiveness than either of the constituent systems alone. This positive combining effect was observed when entire documents were passed between the two retrieval steps, but not when only the expansion terms were passed. Several combinations of primary and secondary retrieval steps were fused using the CombMNZ algorithm; all yielded significant effectiveness improvement over the individual systems, with the best yielding a an improvement of 13% (p = 10-6) over the best individual system and an improvement of 4% (p = 10-5) over a simple fusion of the eight systems.