Conversational Question Answering over Passages by Leveraging Word Proximity Networks

Understand

Question answering (QA) over text passages is a problem of long-standing interest in information retrieval.

• Recently, the conversational setting has attracted attention, where a user asks a sequence of questions to satisfy her information needs around a topic.
• While this setup is a natural one and similar to humans conversing with each other, it introduces two key research challenges: understanding the context left implicit by the user in follow-up questions, and dealing with ad hoc question formulations.
• In this work, we demonstrate CROWN (Conversational passage ranking by Reasoning Over Word Networks): an unsupervised yet effective system for conversational QA with passage responses, that supports several modes of context propagation over multiple turns.