论文标题
建立对话搜索的经济模型
Towards Building Economic Models of Conversational Search
论文作者
论文摘要
文献中已经提出了各种概念和描述性的对话搜索模型 - 尽管有用，但它们并未提供有关代理商和用户之间的相互作用的见解，以应对不同交互的成本和收益。在本文中，我们根据先前在会话搜索会议期间观察到的模式开发了两种经济模型，我们将其称为：首先称为反馈，代理商提出澄清问题，然后提出结果，然后在代理商提出结果后面提出结果，然后提出后续问题。我们的模型表明，给出/请求的反馈量取决于其效率，以改善初始或后续查询以及提供上述反馈的相对成本。这种用于对话搜索的理论框架提供了许多见解，可用于指导和告知会话搜索剂的开发。但是，需要经验工作来估算参数，以便对给定的对话搜索设置进行特定的预测。
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.
