User Input Classification for Chinese Question Answering System

Abstract

Restricted-domain question answering system gives high quality answer to questions within the domain, but gives no response or wrong answer for out of the domain questions. For normal users, the boundary of in-domain and out-domain is unclear. Most users often send out-domain inputs to the restricted-domain question answering system. In such cases, both no answer and wrong answer from the system will yield bad user experience. In this paper, an approach is proposed to solve the bad system response issue of the restricted-domain question answering system. Firstly, it uses a binary classifier to recognize in-domain user inputs and uses the restricted-domain question answering system to proved correct answer. Secondly, an user input taxonomy for out-domain user input is designed, and a classifier is trained to classify the out-domain user input based on the taxonomy. Finally, different response strategies are designed to response to different classes of out-domain user inputs. Experiments and actual application on a restricted-domain question answering system shows that the proposed approach is effective to improve user experience.