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Improvements that don't add up

Published 2 November 2009
Timothy G. Armstrong, Alistair Moffat, William Webber, Justin Zobel
Citations238

TL;DR

This paper analyzes results achieved on the TREC Ad-Hoc, Web, Terabyte, and Robust collections as reported in SIGIR and CIKM and proposes a practice of regular longitudinal comparison to ensure measurable progress, or at least prevent the lack of it from going unnoticed.

Abstract

The existence and use of standard test collections in information retrieval experimentation allows results to be compared between research groups and over time. Such comparisons, however, are rarely made. Most researchers only report results from their own experiments, a practice that allows lack of overall improvement to go unnoticed. In this paper, we analyze results achieved on the TREC Ad-Hoc, Web, Terabyte, and Robust collections as reported in SIGIR (1998--2008) and CIKM (2004--2008). Dozens of individual published experiments report effectiveness improvements, and often claim statistical significance. However, there is little evidence of improvement in ad-hoc retrieval technology over the past decade. Baselines are generally weak, often being below the median original TREC system. And in only a handful of experiments is the score of the best TREC automatic run exceeded. Given this finding, we question the value of achieving even a statistically significant result over a weak baseline. We propose that the community adopt a practice of regular longitudinal comparison to ensure measurable progress, or at least prevent the lack of it from going unnoticed. We describe an online database of retrieval runs that facilitates such a practice.

Keywords

Computer ScienceDecision Sciences