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. Buell
Affiliations:
Louisiana State University, Baton Rouge, LA;Louisiana State University, Baton Rouge, LA
Venue:
SIGIR '84 Proceedings of the 7th annual international ACM SIGIR conference on Research and development in information retrieval
Year:
1984

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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.