Korean Customer Service Associate Assist System Based on Machine Learning
Nayoung Yun, Hakjun Lee, Ji-Won Moon, Ki-Baek Lee · 2019 Third IEEE International Conference on Robotic Computing (IRC) · 2019
We propose a novel system that helps customer service associates answer customers' questions. The algorithm of the proposed system is as follows: First, when a customer asks a question to an associate, the question is transferred to a machine learning based assist system. Then, the system compares the received question to the questions in a predefined FAQ list. After that, the system outputs top five similar questions and the corresponding answers. Finally, the associate selects one question among five recommendations. As a result, additional training data are automatically generated by the selection of the associate, and they are used for re-training of the system. The experimental result shows that the automatically generated data of the proposed system recursively reinforces the accuracy of the system.