全球能源互联网（英文）2021，Vol.4Issue(6)：631-640,10.DOI:10.14171/j.2096-5117.gei.2021.06.010
人工智能在电力客户服务领域的应用
Key technologies of artificial intelligence in electric power customer service
摘要
Abstract
As the demand for customer service continues to increase, more companies are attempting to apply artificial intelligence technology in the field of customer service, enabling intelligent customer service, reducing customer service pressure, and reducing operating costs. Currently, the existing intelligent customer service has a limited degree of intelligence and can only answer simple user questions, and complex user expressions are difficult to understand. To solve the problem of low accuracy of multi-round dialogue semantic understanding, this paper proposes a semantic understanding model based on the fusion of a convolutional neural network (CNN) and attention. The model builds an "intention-slot" joint model based on the "encoding–decoding" framework and uses hidden semantic information that combines intent recognition and slot filling, avoiding the problem of information loss in traditional isolated tasks, and achieving end-to-end semantic understanding. Additionally, an improved attention mechanism based on CNNs is introduced in the decoding process to reduce the interference of redundant information in the original text, thereby increasing the accuracy of semantic understanding. Finally, by applying the model to electric power intelligent customer service, we verified through an experimental comparison that the proposed fusion model improves the performance of intent recognition and slot filling and can improve the user experience of electric power intelligent customer services.关键词
人工智能/客户服务/智能客服语义理解/融合模型Key words
Artificial intelligence/Electric power customer service/Intelligent customer service semantic understanding/Fusion model引用本文复制引用
吴杏平,刘旭生,安业腾..人工智能在电力客户服务领域的应用[J].全球能源互联网（英文）,2021,4(6):631-640,10.基金项目
This work was supported by National Natural Science Foundation of China(No.2018YFB0905000). （No.2018YFB0905000）
