User choices: A new yardstick for the evaluation of ranking algorithms for interactive query expansion

摘要

The performance of eight ranking algorithms was evaluated with respect to their effectiveness in ranking terms for query expansion. The evaluation was conducted within an investigation of interactive query expansion and relevance feedback in a real operational environment. This study focuses on the identification of algorithms that most effectively take cognizance of user preferences. User choices (i.e. the terms selected by the searchers for the query expansion search) provided the yardstick for the evaluation of the eight ranking algorithms. This methodology introduces a user-oriented approach in evaluating ranking algorithms for query expansion in contrast to the standard, system-oriented approaches. Similarities in the performance of the eight algorithms and the ways that these algorithms rank terms were the main focus of this evaluation. The findings demonstrate that the r-lohi, wpq, emim, and porter algorithms have similar performance in bringing good terms to the top of a ranked list of terms for query expansion. However, further evaluation of the algorithms in different (e.g. full-text) environments is needed before these results can be generalized beyond the context of the present study.