Query Performance Prediction By Considering Score Magnitude and Variance Together

Query Performance prediction aims to evaluate the effectiveness of the results returned by a search system in response to a query without any relevance information. In this paper, we propose a method that considers both magnitude and variance of scores of the ranked list of results to measure the performance of a query. Using six different TREC test sets, we compare our predictor with three of the state-of-the-art techniques. The experimental results show that our method is very competitive. Pairwise comparisons with each of the three other methods show that our predictor performs better in more data sets.