User Guidance and System Tuning for Retrieval Sessions

该项目旨在开发用户指导和系统调整的模型和方法，以支持检索会话;实施的方法将在真实的操作检索服务中应用和评估。为此，我们将进行定性和定量分析的检索会话，以获得模型的正式描述这样的会话。基于交互式概率排序原则，这些模型将允许估计交互式检索会话的质量，以及在正在进行的会话期间对有效的检索策略进行预测。这些模型将与改进交互式检索的方法的新实现一起，通过提出有希望的操作（特别是更高级别的搜索活动）来指导用户。为了证明新方法和模型的质量，将进行各种评价。

This project aims at the development of models and methods for user guidance and system tuning for supporting retrieval sessions; the implemented methods will be applied and evaluated in real operating retrieval services. For that, we will perform qualitative and quantitative analyses of retrieval sessions, in order to derive models for the formal description of such sessions. Based on the interactive probability ranking principle, these models will allow for estimating the quality of interactive retrieval sessions, as well as making predictions about effective retrieval strategies during ongoing sessions. Together with new implementations of methods for improving interactive retrieval, these models will be used for guiding users by proposing promising actions, especially higher level search activities. For demonstrating the quality of the new methods and models, various evaluations will be carried out.