Session-Level User Satisfaction Prediction for Customer Service Chatbot in E-Commerce (Student Abstract)

Riheng Yao, Shuangyong Song, Qiudan Li, Chao Wang, Huan Chen, Haiqing Chen, Daniel Dajun Zeng
2020 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
This paper aims to predict user satisfaction for customer service chatbot in session level, which is of great practical significance yet rather untouched. It requires to explore the relationship between questions and answers across different rounds of interactions, and handle user bias. We propose an approach to model multi-round conversations within one session and take user information into account. Experimental results on a dataset from a real-world industrial customer service chatbot Alime
more » ... emonstrate the good performance of our proposed model.
doi:10.1609/aaai.v34i10.7259 fatcat:joiflfqvczfnhi7n4h24iw3oea