Towards Conversational QA: Automatic Identification of Problematic Situations and User Intent

To enable conversational QA, it is important to examine key issues addressed in conversational systems in the context of question answering. In conversational systems, understanding user intent is critical to the success of interaction. Recent studies have also shown that the capability to automatically identify problematic situations during interaction can significantly improve the system performance. Therefore, this paper investigates the new implications of user intent and problematic situations in the context of question answering. Our studies indicate that, in basic interactive QA, there are different types of user intent that are tied to different kinds of system performance (e.g., problematic/error free situations). Once users are motivated to find specific information related to their information goals, the interaction context can provide useful cues for the system to automatically identify problematic situations and user intent.

• Type: Conference
• Year: 2006
• Where: ACL
• Authors: Joyce Y. Chai, Chen Zhang, Tyler Baldwin
• Keywords: ACL 2006, ACL 2007, Conversational Systems, Problematic Situations, User Intent