Optimization Algorithm of Power Marketing AI Response System in the Era of Intelligent Technology

The intelligent question and answer platform can improve customer satisfaction, strengthen the self-service function of customers, and obtain business information conveniently and quickly. It is an effective means to reduce the company's overall operating costs and an important measure to promote the capacity building of remote service channels. The purpose of this paper is to study the optimization algorithm of the power marketing AI response system based on the era of intelligent technology. Combined with knowledge graph visualization and other technical means, the basic knowledge graph of the power industry is constructed, and an intelligent dialogue system is designed in combination with the constructed knowledge graph to help the power industry's customer service capabilities to improve, knowledge storage, knowledge management and other work to be carried out well. From the perspective of model evaluation indicators, this paper chooses the accuracy of the model as an important indicator to measure the efficiency of the model. In the relational classification model of information extraction, the comprehensive indicators of precision, recall, and F1 value of the BERT-BiLSTM-CRF knowledge extraction model are better than word embedding + BiLSTM + CRF.