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Advances in a Bayesian decision model of user stopping behavior for scanning the output of an information retrieval system

Authors:

Donald H. Kraft,

Duncan A. BuellAuthors Info & Claims

SIGIR '84: Proceedings of the 7th annual international ACM SIGIR conference on Research and development in information retrieval

Pages 421 - 433

Published: 02 July 1984 Publication History

Abstract

The formal modeling of information storage and retrieval systems has been an important element in the analysis and design of these systems. The retrieval mechanism has been viewed as a probablistic decision problem, often involving utilities. One key element is the evaluation of such retrieval systems. In this paper, we focus on the impact of the stopping rule, which determines when the user chooses to stop scanning the list of records retrieved in response to a given query. We shall first trace the evolution of the modelling and use of the stopping rule approach. Then, we shall briefly report on some recent results in our attempt to better model the generation of stopping rules.

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Cited By

Toms EFreund LAllan JAslam JSanderson MZhai CZobel J(2009)Predicting stopping behaviourProceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval10.1145/1571941.1572110(750-751)Online publication date: 19-Jul-2009
https://dl.acm.org/doi/10.1145/1571941.1572110

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Information & Contributors

Information

Published In

cover image ACM Conferences

SIGIR '84: Proceedings of the 7th annual international ACM SIGIR conference on Research and development in information retrieval

July 1984

422 pages

ISBN:0521268656

Conference Chair:
A. S. Pollitt

Sponsors

ACM: Association for Computing Machinery
British Computer Society

Publisher

BCS Learning & Development Ltd.

Swindon, United Kingdom

Publication History

Published: 02 July 1984

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Cited By

Toms EFreund LAllan JAslam JSanderson MZhai CZobel J(2009)Predicting stopping behaviourProceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval10.1145/1571941.1572110(750-751)Online publication date: 19-Jul-2009
https://dl.acm.org/doi/10.1145/1571941.1572110

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