Enhancing Information-Seeking Conversations with Query-Bag Pseudo Relevance Feedback

The core message of this paper is to propose a Query-bag Pseudo Relevance Feedback (QB-PRF) framework that can effectively enhance the performance of information-seeking conversation systems. The framework includes a Query-bag Selection Module (QBS) to retrieve and select relevant queries to form a query-bag, and a Query-bag Fusion Module (QBF) to fuse the query-bag information with the original query to improve the query representation.