Effect of dynamic pruning safety on learning to rank effectiveness

Macdonald, C. , Tonellotto, N. and Ounis, I. (2012) Effect of dynamic pruning safety on learning to rank effectiveness. In: SIGIR 2012: 35th Annual International ACM SIGIR Conference on Research and Development on Information Retrieval, Portland OR, USA, 12-16 Aug 2012, pp. 1051-1052. (doi: 10.1145/2348283.2348464)

Full text not currently available from Enlighten.

Publisher's URL: http://dx.doi.org/10.1145/2348283.2348464


A dynamic pruning strategy, such as WAND, enhances retrieval efficiency without degrading effectiveness to a given rank K, known as safe-to-rank-K. However, it is also possible for WAND to obtain more efficient but unsafe retrieval without actually significantly degrading effectiveness. On the other hand, in a modern search engine setting, dynamic pruning strategies can be used to efficiently obtain the set of documents to be re-ranked by the application of a learned model in a learning to rank setting. No work has examined the impact of safeness on the effectiveness of the learned model. In this work, we investigate the impact of WAND safeness through experiments using 150 TREC Web track topics. We find that unsafe WAND is biased towards documents with lower docids, thereby impacting effectiveness.

Item Type:Conference Proceedings
Additional Information:ISBN: 9781450314725
Glasgow Author(s) Enlighten ID:Macdonald, Professor Craig and Ounis, Professor Iadh
Authors: Macdonald, C., Tonellotto, N., and Ounis, I.
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
College/School:College of Science and Engineering > School of Computing Science

University Staff: Request a correction | Enlighten Editors: Update this record