Streamlining Evaluation with ir-measures

MacAvaney, S. , Macdonald, C. and Ounis, I. (2022) Streamlining Evaluation with ir-measures. In: 44th European Conference on Information Retrieval (ECIR 2022), Stavanger, Norway, 10-14 Apr 2022, pp. 305-310. ISBN 9783030997359 (doi: 10.1007/978-3-030-99739-7_38)

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259597.pdf - Accepted Version



We present ir-measures, a new tool that makes it convenient to calculate a diverse set of evaluation measures used in information retrieval. Rather than implementing its own measure calculations, ir-measures provides a common interface to a handful of evaluation tools. The necessary tools are automatically invoked (potentially multiple times) to calculate all the desired metrics, simplifying the evaluation process for the user. The tool also makes it easier for researchers to use recently-proposed measures (such as those from the C/W/L framework) alongside traditional measures, potentially encouraging their adoption.

Item Type:Conference Proceedings
Additional Information:We acknowledge EPSRC grant EP/R018634/1: Closed-Loop Data Science for Complex, Computationally- & Data-Intensive Analytics.
Glasgow Author(s) Enlighten ID:MacAvaney, Dr Sean and Macdonald, Professor Craig and Ounis, Professor Iadh
Authors: MacAvaney, S., Macdonald, C., and Ounis, I.
College/School:College of Science and Engineering > School of Computing Science
Published Online:05 April 2022
Copyright Holders:Copyright © 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
First Published:First published in Advances in Information Retrieval. ECIR 2022. Lecture Notes in Computer Science, vol 13186
Publisher Policy:Reproduced in accordance with the publisher copyright policy
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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
300982Exploiting Closed-Loop Aspects in Computationally and Data Intensive AnalyticsRoderick Murray-SmithEngineering and Physical Sciences Research Council (EPSRC)EP/R018634/1Computing Science