In order to improve the level of electricity consumption, it is an inevitable trend to use artificial intelligence technology to provide active service to electricity customers. Under the background, an active customer service recommendation method is proposed based on LSTM-Attention fusion considering the lack of research on active customer service in the power industry. The proposed method can effectively solve the problems of gradient mass and gradient explosion in the service recommendation of a single deep learning model. Firstly, a model is established for extracting potential service demands of customers from electric power complaint work orders. Then, an active service recommendation method is obtained for electric power customers based on the LSTM-Attention fusion algorithm. Finally, an electric power customer complaint work order in one city is included to verify the algorithm and model. It is shown that this method is effective.
张帝,王韬,朱吉然,唐海国,张志丹,唐小伟,颜宏文.基于LSTM-Attention融合的电力客户主动服务推荐方法[J].电力科学与技术学报,2022,(2):213-218. ZHANG Di, WANG Tao, ZHU Jiran, TANG Haiguo, ZHANG Zhidan, TANG Xiaowei, YAN Hongwen. Active service recommendation method for power customers based on LSTM-Attention fusion[J]. Journal of Electric Power Science and Technology,2022,(2):213-218.复制