Sequential Testing for Early Stopping of Online Experiments

Kharitonov, E., Vorobev, A., Macdonald, C. , Serdyukov, P. and Ounis, I. (2015) Sequential Testing for Early Stopping of Online Experiments. In: 38th Annual ACM SIGIR Conference (SIGIR 2015), Santiago, Chile, 9-13 Aug 2015, pp. 473-482. ISBN 9781450336215 (doi: 10.1145/2766462.2767729)

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Abstract

Online evaluation methods, such as A/B and interleaving experiments, are widely used for search engine evaluation. Since they rely on noisy implicit user feedback, running each experiment takes a considerable time. Recently, the problem of reducing the duration of online experiments has received substantial attention from the research community. However, the possibility of using sequential statistical testing procedures for reducing the time required for the evaluation experiments remains less studied. Such sequential testing procedures allow an experiment to stop early, once the data collected is sufficient to make a conclusion. In this work, we study the usefulness of sequential testing procedures for both interleaving and A/B testing. We propose modified versions of the O'Brien & Fleming and MaxSPRT sequential tests that are applicable for testing in the interleaving scenario. Similarly, for A/B experiments, we assess the usefulness of the O'Brien & Fleming test, as well as that of our proposed MaxSPRT-based sequential testing procedure. In our experiments on datasets containing 115 interleaving and 41 A/B testing experiments, we observe that considerable reductions in the average experiment duration can be achieved by using our proposed tests. In particular, for A/B experiments, the average experiment durations can be reduced by up to 66% in comparison with a single step test procedure, and by up to 44% in comparison with the O'Brien & Fleming test. Similarly, a marked relative reduction of 63% in the duration of the interleaving experiments can be achieved.

Item Type:Conference Proceedings
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Macdonald, Professor Craig and Ounis, Professor Iadh
Authors: Kharitonov, E., Vorobev, A., Macdonald, C., Serdyukov, P., and Ounis, I.
College/School:College of Science and Engineering > School of Computing Science
ISBN:9781450336215
Copyright Holders:Copyright © 2015 ACM
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

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