Evaluating Evaluation Measures with Worst-Case Confidence Interval Widths

Tetsuya Sakai
2017 NTCIR Conference on Evaluation of Information Access Technologies  
IR evaluation measures are o en compared in terms of rank correlation between two system rankings, agreement with the users' preferences, the swap method, and discriminative power. While we view the agreement with real users as the most important, this paper proposes to use the Worst-case Con dence interval Width (WCW) curves to supplement it in test-collection environments. WCW is the worst-case width of a con dence interval (CI) for the di erence between any two systems, given a topic set
more » ... . We argue that WCW curves are more useful than the swap method and discriminative power, since they provide a statistically well-founded overview of the comparison of measures over various topic set sizes, and visualise what levels of di erences across measures might be of practical importance. First, we prove that Sakai's ANOVA-based topic set size design tool can be used for discussing WCW instead of his CI-based tool that cannot handle large topic set sizes. We then provide some case studies of evaluating evaluation measures using WCW curves based on the ANOVA-based tool, using data from TREC and NTCIR.
dblp:conf/ntcir/Sakai17 fatcat:gul3wm7conheppwz5sfcy2zcba