Visible to the public Sensitive and Scalable Online Evaluation with Theoretical Guarantees

TitleSensitive and Scalable Online Evaluation with Theoretical Guarantees
Publication TypeConference Paper
Year of Publication2017
AuthorsOosterhuis, Harrie, de Rijke, Maarten
Conference NameProceedings of the 2017 ACM on Conference on Information and Knowledge Management
PublisherACM
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-4918-5
KeywordsCollaboration, composability, Human Behavior, human factor, information retrieval, information theoretic security, Metrics, multileaving, online evaluation, policy, pubcrawl, ranker evaluation, Resiliency, Scalability, theoretical guarantees
AbstractMultileaved comparison methods generalize interleaved comparison methods to provide a scalable approach for comparing ranking systems based on regular user interactions. Such methods enable the increasingly rapid research and development of search engines. However, existing multileaved comparison methods that provide reliable outcomes do so by degrading the user experience during evaluation. Conversely, current multileaved comparison methods that maintain the user experience cannot guarantee correctness. Our contribution is two-fold. First, we propose a theoretical framework for systematically comparing multileaved comparison methods using the notions of considerateness, which concerns maintaining the user experience, and fidelity, which concerns reliable correct outcomes. Second, we introduce a novel multileaved comparison method, Pairwise Preference Multileaving (PPM), that performs comparisons based on document-pair preferences, and prove that it is considerate and has fidelity. We show empirically that, compared to previous multileaved comparison methods, PPM is more sensitive to user preferences and scalable with the number of rankers being compared.
URLhttp://doi.acm.org/10.1145/3132847.3132895
DOI10.1145/3132847.3132895
Citation Keyoosterhuis_sensitive_2017