Boosting a Rule-Based Chatbot Using Statistics and User Satisfaction Ratings

Using data from user-chatbot conversations where users have rated the answers as good or bad, we propose a more efficient alternative to a chatbot’s keyword-based answer retrieval heuristic. We test two neural network approaches to the near-duplicate question detection task as a first step towards a better answer retrieval method. A convolutional neural network architecture gives promising results on this difficult task.