The TREC-8 Query Track.

The Query Track in TREC-8 is an attempt to gather enough information from a large number of systems on aLarge number of queries to be able to start understanding query variability, which presents a great opportunity for improving system performance.

Abstract

The Query Track in TREC-8 is a bit different from all the other tracks. It is a cooperative effort among the participating groups to look at the issue of “query variability.” The evaluation averages presented in a typical system evaluation task, such as the TREC Ad-Hoc Task, conceal a tremendous variability of system performance across topics/queries. No system can possibly perform equally well on all topics: some information needs (expressed by topics) are harder than others. But what is quite surprising, especially to people just starting to look at IR, is the large variability in system performance across topics as compared to other systems. In a typical TREC task, no system is the best for all the topics in the task. It is extremely rare for any system to be above average for all the topics. Instead, the best system is normally above average for most of the topics, and best for maybe 5%-10% of the topics. It very often happens that quite below-average systems are also best for 5%-10% of the topics, but do poorly on the other topics. The Average Precision Histograms presented on the TREC evaluation result pages are an attempt to show what is happening at the individual topic level. This large topic/query variability presents a great opportunity for improving system performance. If we can understand why some systems do well on some queries but poorly on others, then we can start introducing query dependent processing to improve results on those poor performance queries. Unfortunately, we just don’t have enough information from the results of a typical TREC task to really understand what is happening. The results on 50 to 150 queries are just not enough to draw any conclusions. The Query Track at TREC is an attempt to gather enough information from a large number of systems on a large number of queries to be able to start understanding query variability.