Context-Aware, Adaptive Information Retrieval for Investigative Tasks

We are building an intelligent information system to aid users in their investigative tasks, such as detecting fraud. In such a task, users must progressively search and analyze relevant information before drawing a conclusion. In this paper, we address how to help users find relevant information during an investigation. Specifically, we present a novel approach that can improve information retrieval by exploiting a user's investigative context. Compared to existing retrieval systems, which are either context insensitive or leverage only limited user context, Our work offers two unique contributions. First, our system works with users cooperatively to build an investigative context, which is otherwise very difficult to capture by machine or human alone. Second, we develop a context-aware method that can adaptively retrieve and evaluate information relevant to an ongoing investigation. Experiments show that our approach can improve the relevance of retrieved information significantly. As a result, users can fulfill their investigative tasks more efficiently and effectively.