An E-Commerce Customer Service Robot Based on Intention Recognition Model

Minjing Peng, Yanwei Qin, Chenxin Tang and Xiangming Deng
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Minjing Peng: School of Economics and Management, Wuyi University, Guangdong, China
Yanwei Qin: Research Center of E-Commerce Augmented Reality of Guangdong Province, Wuyi University, Guangdong, China
Chenxin Tang: School of Economics and Management, Wuyi University, Guangdong, China
Xiangming Deng: Research Center of E-Commerce Augmented Reality of Guangdong Province, Wuyi University, Guangdong, China

Journal of Electronic Commerce in Organizations (JECO), 2016, vol. 14, issue 1, 34-44

Abstract: There are three defects for providing human-labor customer services in e-commerce operations: high costs of human labors, staff turnover, and lack of service quality assurance. Breakthroughs made in artificial intelligence, natural language processing and related fields make it possible to replace human labors with online artificial intelligent robots to provide the e-commerce customer service, which indicates the online robots are the future of e-commerce customer services. However, most of the current robots are designed to reply with knowledge matching the key words in question sentences from the database, rarely involving in research on customer intentions that are key factors influencing user experience and online sales. In this research, an intention recognizing model was proposed to obtain intentions of e-commerce consumers by computing the strengths of candidate intention nodes in the intention graph, which was used to describe relations between different goods that could be the intentional targets of e-commerce consumers. The proposed robot was constructed based on the intention recognizing model to identify intentions of consumers and use the located knowledge combined with the AIML based sentence composition template to produce the response sentences for consumers. At last, the proposed robot was evaluated using F3 and ROUGE metrics by comparing with a keyword matching robot. And the evaluation results proved the validity of the proposed robot.

Date: 2016
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