Alternatives to Bpref

  • Authors:
  • Tetsuya Sakai

  • Affiliations:
  • NewsWatch, Inc. (current affiliation)/Toshiba Corporate R&D Center

  • Venue:
  • SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
  • Year:
  • 2007

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Abstract

Recently, a number of TREC tracks have adopted a retrieval effectiveness metric called bpref which has been designed for evaluation environments with incomplete relevance data. A graded-relevance version of this metric called rpref has also been proposed. However, we show that the application of Q-measure, normalised Discounted Cumulative Gain (nDCG) or Average Precision (AveP)to condensed lists, obtained by ?ltering out all unjudged documents from the original ranked lists, is actually a better solution to the incompleteness problem than bpref. Furthermore, we show that the use of graded relevance boosts the robustness of IR evaluation to incompleteness and therefore that Q-measure and nDCG based on condensed lists are the best choices. To this end, we use four graded-relevance test collections from NTCIR to compare ten different IR metrics in terms of system ranking stability and pairwise discriminative power.