This paper analyzes the total movement period of the development of the world telecommunication industry,and points out the basic principles of the supply and demand regulation and the market drive are important and u...This paper analyzes the total movement period of the development of the world telecommunication industry,and points out the basic principles of the supply and demand regulation and the market drive are important and useful to the telecommunication industry.The thesis puts forward the pertinent evaluation and the positive suggestions according to the general characteristics and individual characteristics of Chinese telecommunication industry and emphasizes the meaning of the demand drive.展开更多
In the age of information explosion,big data has brought challenges but also great opportunities that support a wide range of applications for people in all walks of life.Faced with the continuous and intense competit...In the age of information explosion,big data has brought challenges but also great opportunities that support a wide range of applications for people in all walks of life.Faced with the continuous and intense competition from OTT service providers,traditional telecommunications service providers have been forced to undergo enterprise transformation.Fortunately,these providers have natural and unique advantages in terms of both data sources and data scale,all of which give them a competitive advantage.Multiple foreign mainstream telecom operators have already applied big data for their own growth,from internal business to external applications.Armed with big data,domestic telecom companies are also innovating business models.This paper will introduce three aspects of big data in the telecommunications industry.First,the unique characteristics and advantages of communications industry big data are discussed.Second,the development of the big data platform architecture is introduced in detail,which incorporates ve crucial sub-systems.We highlight the data collection and data processing systems.Finally,three internal or external application areas based on big data analysis are discussed,namely basic business,network construction,and intelligent tracing.Our work sheds light on how to deal with big data for telecommunications enterprise development.展开更多
In response to the challenges of complex multi-agent responsibility division and low efficiency in manual judgment in telecommunications operators’customer complaint handling,this paper proposes a multi-agent interac...In response to the challenges of complex multi-agent responsibility division and low efficiency in manual judgment in telecommunications operators’customer complaint handling,this paper proposes a multi-agent interaction responsibility determination method based on Large Language Models(LLMs)and Prompt Engineering.Taking complaint texts as input,the method constructs a hierarchical reasoning framework consisting of an individual layer and an interaction layer.The individual layer analyzes each agent’s responsibility fulfillment behavior,while the interaction layer depicts responsibility transfer relationships among agents.A responsibility fusion mechanism then integrates these analyses to generate a comprehensive responsibility distribution.This method achieves automated and interpretable multi-agent responsibility determination,offering a new technical approach and theoretical foundation for intelligent customer service,responsibility tracing,and service quality evaluation.展开更多
文摘This paper analyzes the total movement period of the development of the world telecommunication industry,and points out the basic principles of the supply and demand regulation and the market drive are important and useful to the telecommunication industry.The thesis puts forward the pertinent evaluation and the positive suggestions according to the general characteristics and individual characteristics of Chinese telecommunication industry and emphasizes the meaning of the demand drive.
基金supported partially by Key Program of National Natural Science Foundation of China(No.61631018)the Funda-mental Research Funds for the Central Universities and Huawei Technology Innovative Research on Wireless Big Data.
文摘In the age of information explosion,big data has brought challenges but also great opportunities that support a wide range of applications for people in all walks of life.Faced with the continuous and intense competition from OTT service providers,traditional telecommunications service providers have been forced to undergo enterprise transformation.Fortunately,these providers have natural and unique advantages in terms of both data sources and data scale,all of which give them a competitive advantage.Multiple foreign mainstream telecom operators have already applied big data for their own growth,from internal business to external applications.Armed with big data,domestic telecom companies are also innovating business models.This paper will introduce three aspects of big data in the telecommunications industry.First,the unique characteristics and advantages of communications industry big data are discussed.Second,the development of the big data platform architecture is introduced in detail,which incorporates ve crucial sub-systems.We highlight the data collection and data processing systems.Finally,three internal or external application areas based on big data analysis are discussed,namely basic business,network construction,and intelligent tracing.Our work sheds light on how to deal with big data for telecommunications enterprise development.
文摘In response to the challenges of complex multi-agent responsibility division and low efficiency in manual judgment in telecommunications operators’customer complaint handling,this paper proposes a multi-agent interaction responsibility determination method based on Large Language Models(LLMs)and Prompt Engineering.Taking complaint texts as input,the method constructs a hierarchical reasoning framework consisting of an individual layer and an interaction layer.The individual layer analyzes each agent’s responsibility fulfillment behavior,while the interaction layer depicts responsibility transfer relationships among agents.A responsibility fusion mechanism then integrates these analyses to generate a comprehensive responsibility distribution.This method achieves automated and interpretable multi-agent responsibility determination,offering a new technical approach and theoretical foundation for intelligent customer service,responsibility tracing,and service quality evaluation.
