This article presents the emerging topic of dynamic search (DS). To position dynamic search in a larger research landscape, the article discusses in detail its relationship to related research topics and disciplines. The article reviews approaches to modeling dynamics during information seeking, with an emphasis on Reinforcement Learning (RL)-enabled methods. Details are given for how different approaches are used to model interactions among the human user, the search system, and the environment. The paper ends with a review of evaluations of dynamic search systems.
翻译:本条介绍了新兴的动态搜索(DS)专题。为了将动态搜索定位在更大的研究领域,文章详细讨论了其与相关研究专题和学科的关系。文章回顾了信息搜索期间的动态建模方法,重点是强化学习(RL)驱动的方法。详细介绍了如何使用不同方法模拟人类用户、搜索系统和环境之间的互动。本文最后回顾了动态搜索系统的评价。