Automatic ranking of retrieval systems in imperfect environments

ABSTRACT

The empirical investigation of the effectiveness of information retrieval (IR) systems requires a test collection, a set of query topics, and a set of relevance judgments made by human assessors for each query. Previous experiments show that differences in human relevance assessments do not affect the relative performance of retrieval systems. Based on this observation, we propose and evaluate a new approach to replace the human relevance judgments by an automatic method. Ranking of retrieval systems with our methodology correlates positively and significantly with that of human-based evaluations. In the experiments, we assume a Web-like imperfect environment: the indexing information for all documents is available for ranking, but some documents may not be available for retrieval. Such conditions can be due to document deletions or network problems. Our method of simulating imperfect environments can be used for Web search engine assessment and in estimating the effects of network conditions (e.g., network unreliability) on IR system performance.

References

1. Chowdhury A., Soboroff I. Automatic evaluation of World Wide Web search services. In the Proceedings of the 2002 ACM SIGIR Conference, 421--422.
2. Voorhees E.M., Harman, D. Overview of the Fifth Text Retrieval Conference (TREC-5). In E. M. Voorhees and D.K. Harman, editors, The Fifth Text Retrieval Conference, NIST Special Publication 500-238. National Institute of Standards and Technology, Gaithersburg, MD, November 1996.
3. Soboroff, I., Nicholas,C., Cahan, P. Ranking Retrieval Systems without Relevance Judgments. In the Proceedings of the 2001 ACM SIGIR Conference, 66--73.

Index Terms

• Information systems

  • Information retrieval

    • Evaluation of retrieval results

    • Information retrieval query processing