TY  - GEN
TI  - The impact of fixed-cost pooling strategies on test collection bias
EP  - 108
Y1  - 2016/09/12/
AV  - public
SP  - 105
N1  - This version is the author accepted manuscript. For information on re-use, please refer to the publisher?s terms and conditions.
ID  - discovery10059980
N2  - In Information Retrieval, test collections are usually built using the pooling method. Many pooling strategies have been developed for the pooling method. Herein, we address the question of identifying the best pooling strategy when evaluating systems using precision-oriented measures in presence of budget constraints on the number of documents to be evaluated. As a quality measurement we use the bias introduced by the pooling strategy, measured both in terms of Mean Absolute Error of the scores and in terms of ranking errors. Based on experiments on 15 test collections, we conclude that, for precision-oriented measures, the best strategies are based on Rank-Biased Precision (RBP). These results can inform collection builders because they suggest that, under fixed assessment budget constraints, RBP-based sampling produces less biased pools than other alternatives.
UR  - https://doi.org/10.1145/2970398.2970429
PB  - ACM
CY  - New York, USA
KW  - Pooling Method
KW  -  Pooling Strategies
KW  -  Pool Bias
A1  - Lipani, A
A1  - Zuccon, G
A1  - Lupu, M
A1  - Koopman, B
A1  - Hanbury, A
T3  - ACM International Conference on the Theory of Information Retrieval
ER  -