Towards building economic models of conversational search

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Azzopardi, Leif and Aliannejadi, Mohammad and Kanoulas, Evangelos; Hagen, Matthias and Verberne, Suzan and Macdonald, Craig and Seifert, Christin and Balog, Krisztian and Nørvåg, Kjetil and Setty, Vinay, eds. (2022) Towards building economic models of conversational search. In: Advances in Information Retrieval - 44th European Conference on IR Research, ECIR 2022, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) . Springer, NOR, pp. 31-38. ISBN 9783030997380 (https://doi.org/10.1007/978-3-030-99739-7_4)

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Abstract

Various conceptual and descriptive models of conversational search have been proposed in the literature – while useful, they do not provide insights into how interaction between the agent and user would change in response to the costs and benefits of the different interactions. In this paper, we develop two economic models of conversational search based on patterns previously observed during conversational search sessions, which we refer to as: Feedback First where the agent asks clarifying questions then presents results, and Feedback After where the agent presents results, and then asks follow up questions. Our models show that the amount of feedback given/requested depends on its efficiency at improving the initial or subsequent query and the relative cost of providing said feedback. This theoretical framework for conversational search provides a number of insights that can be used to guide and inform the development of conversational search agents. However, empirical work is needed to estimate the parameters in order to make predictions specific to a given conversational search setting.

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