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

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

Minjing Peng, Yanwei Qin, Chenxin Tang, Xiangming Deng
Copyright: © 2016 |Volume: 14 |Issue: 1 |Pages: 11
ISSN: 1539-2937|EISSN: 1539-2929|EISBN13: 9781466688940|DOI: 10.4018/JECO.2016010104
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MLA

Peng, Minjing, et al. "An E-Commerce Customer Service Robot Based on Intention Recognition Model." JECO vol.14, no.1 2016: pp.34-44. http://doi.org/10.4018/JECO.2016010104

APA

Peng, M., Qin, Y., Tang, C., & Deng, X. (2016). An E-Commerce Customer Service Robot Based on Intention Recognition Model. Journal of Electronic Commerce in Organizations (JECO), 14(1), 34-44. http://doi.org/10.4018/JECO.2016010104

Chicago

Peng, Minjing, et al. "An E-Commerce Customer Service Robot Based on Intention Recognition Model," Journal of Electronic Commerce in Organizations (JECO) 14, no.1: 34-44. http://doi.org/10.4018/JECO.2016010104

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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.

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