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From a User Model for Query Sessions to Session Rank Biased Precision (sRBP)

Lipani, A; Carterette, B; Yilmaz, E; (2019) From a User Model for Query Sessions to Session Rank Biased Precision (sRBP). In: The 5th ACM SIGIR International Conference on the Theory of Information Retrieval. (pp. pp. 109-116). ACM: Santa Clara, CA, USA. Green open access

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Abstract

To satisfy their information needs, users usually carry out searches on retrieval systems by continuously trading off between the examination of search results retrieved by under-specified queries and the refinement of these queries through reformulation. In Information Retrieval (IR), a series of query reformulations is known as a query-session. Research in IR evaluation has traditionally been focused on the development of measures for the ad hoc task, for which a retrieval system aims to retrieve the best documents for a single query. Thus, most IR evaluation measures, with a few exceptions, are not suitable to evaluate retrieval scenarios that call for multiple refinements over a query-session. In this paper, by formally modeling a user’s expected behaviour over query-sessions, we derive a session-based evaluation measure, which results in a generalization of the evaluation measure Rank Biased Precision (RBP). We demonstrate the quality of this new session-based evaluation measure, named Session RBP (sRBP), by evaluating its user model against the observed user behaviour over the query-sessions of the 2014 TREC Session track

Type: Proceedings paper
Title: From a User Model for Query Sessions to Session Rank Biased Precision (sRBP)
Event: The 5th ACM SIGIR International Conference on the Theory of Information Retrieval
Location: Santa Clara, California
Dates: 02 October 2019 - 05 October 2019
Open access status: An open access version is available from UCL Discovery
DOI: 10.1145/3341981.3344216
Publisher version: https://doi.org/10.1145/3341981.3344216
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: session search, retrieval evaluation, user model, sRBP
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10081529
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