User Guidance and System Tuning for Retrieval Sessions

该项目旨在为支持检索会议开发用户指导和系统调整的模型和方法；所实现的方法将在实际操作的检索服务中得到应用和评价。为此，我们将执行检索会话的定性和定量分析，以便为这些会话的正式描述导出模型。基于交互概率排序原则，这些模型将允许估计交互检索会话的质量，以及在正在进行的会话中对有效的检索策略做出预测。与改进交互检索的新方法一起，这些模型将用于通过提出有希望的操作来指导用户，特别是更高级别的搜索活动。为了证明新方法和模型的质量，将进行各种评估。

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.