We are developing a novel wearable devices called the urban intelligent fashion advertising.Such system is mobile information devices capable of supporting remote communication and intelligent interaction between term...We are developing a novel wearable devices called the urban intelligent fashion advertising.Such system is mobile information devices capable of supporting remote communication and intelligent interaction between terminals.In this paper,we explore the possible functions of such a wearable devices and will present the service-based architecture combing the hardware and the software.This architecture involves two major parts.The first part is hardware design,which includes microcontroller,display part,communication module,and positioning system module.The second part is software design,which is a real-time interactive system that includes signal reception,position detection,and user workload assessment.Then,we use the interactive concept and interactive technology to construct the urban fashion advertising service model,and elaborate on its business model.Finally,we present sustainability development recommendations for the proposed service model.展开更多
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 custom...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.展开更多
基金supported by the National Natural Science Foundation of China under the grant number 51541503,50775165,and 51775389the project of Hubei Digital Textile Equipment Key Laboratory DTL2016004.
文摘We are developing a novel wearable devices called the urban intelligent fashion advertising.Such system is mobile information devices capable of supporting remote communication and intelligent interaction between terminals.In this paper,we explore the possible functions of such a wearable devices and will present the service-based architecture combing the hardware and the software.This architecture involves two major parts.The first part is hardware design,which includes microcontroller,display part,communication module,and positioning system module.The second part is software design,which is a real-time interactive system that includes signal reception,position detection,and user workload assessment.Then,we use the interactive concept and interactive technology to construct the urban fashion advertising service model,and elaborate on its business model.Finally,we present sustainability development recommendations for the proposed service model.
基金supported by National Natural Science Foundation of China(No.2018YFB0905000).
文摘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.
