基于用户画像的智能电力客服系统容错服务组合优化模型

Fault Tolerant Service Composition Optimization Model of Intelligent Power Customer Service System Based on User Portrait

针对渠道内电力客服系统容错特征数据超出运行约定范围,导致智能系统服务器群集负载均衡速率过低的问题,研究了基于用户画像的智能电力客服系统容错服务组合优化模型。基于用户画像,设计了智能电力客服系统容错服务组合优化模型,根据数据更新机制统一渠道信息的分类结果,扩展智能电力客服系统容错服务优化渠道。在运行约定范围内,进行渠道内特征数据自启,基于用户画像分析优化渠道内系统容错特征数据,对电力客服系统容错服务函数进行设计,设计函数的变换矩阵,建立电力客服系统容错服务效能模型。分析实验结果显示该方法的服务器群集负载均衡速率最低为50.00 kb/s,容错效能平稳,容错服务组合优化模型效果得到保证,解决了服务器群集负载均衡速率过低的问题。

Aiming at the problem that the fault-tolerant characteristic data of the power customer service system in the channel is beyond the agreed range, which leads to the low load balancing rate of the intelligent system server cluster, this paper studies the fault-tolerant service composition optimization model of the intelligent power customer service system based on the user portrait. Based on the user portrait, a fault-tolerant service composition optimization model of intelligent power customer service system is designed. According to the data update mechanism, the classification results of channel information are unified, and the fault-tolerant service optimization channel of intelligent power customer service system is expanded. The fault-tolerant service function of the power customer service system is designed based on the user portrait analysis and optimization of the fault-tolerant characteristic data of the system in the channel. The transformation matrix of the function is designed, and the fault-tolerant service efficiency model of the power customer service system is established. Experimental results show that the minimum load balancing rate of server cluster is 50.00 kb/s, the fault-tolerant performance is stable, the effect of fault-tolerant service composition optimization model is guaranteed, and the problem of low load balancing rate of server cluster is solved.