Leather personalized study design in intelligent customization

The rich and colorful leather design brings a broad stage of fashion design in the past, China＇s leather （leather） clothing brand single, old style, color： black, blue, is brown. The economic and cultural development, leading the fashion changes, the concept is also constantly promote the development of a new direction, to the consumer, aesthetic with the change of consumption concept, the fur （leather） apparel consumption presents a civilian, personalized, ideal trend, leather （leather） clothing to reflects personal charm and style of the clothing style, design aesthetic appreciation, knowledge and other aspects of the new technology and new materials to absorb human body art is to stimulate leather （leather） the change of clothing. With the continuous development of science and technology, intelligent garment customization to the majority of consumers, the effect of intelligent custom fur （leather） three direction costumes （fabrics, colors, styles） for innovative research, get a Of leather （leather） costumes to break the current leather （leather） styles of dull shape, rich leather （leather） and other clothing charm, for the fur （leather） costumes to all ages personality need to provide ideas and new development space.

Key technologies of artificial intelligence in electric power customer service

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.

Research of CRM Based on Customer Intelligence Engine

The discipline of business intelligence addresses a broad range of functional activities from data mining and statistical analysis to predictive modeling and reporting, and customer intelligence is the actionable output from an intelligence eco-system. In order to focus enterprise's attention on their customers satisfaction in the customer relationship management and make CRM system run more efficiently, a new concept of customer intelligence engine(CIE) is proposed at first time in the paper, the architecture of CIE is structured, the trigger of CIE is defined and described, the CIE-based CRM eco-system is also discussed.