Conference Proceedings

Can Users Predict Relative Query Effectiveness?

O Zendel, MP Ebrahim, JS Culpepper, A Moffat, F Scholer

SIGIR 2022 - Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval | Association for Computing Machinery | Published : 2022

Abstract

Any given information need can be expressed via a wide range of possible queries. Recent work with such query variations has demonstrated that different queries can fetch notably divergent sets of documents, even when the queries have identical intents and superficial similarity. That is, different users might receive SERPs of quite different effectiveness for the same information need. That observation then raises an interesting question: do users have a sense of how useful any given query will be? Can they anticipate the effectiveness of alternative queries for the same retrieval need? To explore that question we designed and carried out a crowd-sourced user study in which we asked subject..

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University of Melbourne Researchers

Grants

Awarded by Australian Research Council


Funding Acknowledgements

We thank the reviewers for their comments. This work was supported by the Australian Research Council's Discovery Projects Scheme (grant DP190101113). Code and data are available from https://github.com/Zendelo/cs-qpp.