With never-ending changes and improvements and an increasing industrial scale of the Internet, the emerging new application trends, such as social networking, network video, intelligent search and mobile Internet, and...With never-ending changes and improvements and an increasing industrial scale of the Internet, the emerging new application trends, such as social networking, network video, intelligent search and mobile Internet, and new Internet technologies, such as Mashup, artificial intelligence, grid computing and open platform, are significantly influencing the Internet industrial structure. Moreover, the rapid development of the Internet and the convergence of the Internet and telecom networks, especially the development of mobile Internet, are giving the telecom industry a shock. This shock will certainly change the structure of the telecom industry, gradually break the monopoly status of telecom operators, shift the telecom emphasis to services and contents, and enhance the importance of terminal vendors in the industrial chain.展开更多
The long-awaited ITU Telecom World 2006 is to open in Hong Kong. It is no doubt that the hosting of this pageant in Hong Kong proves the praise and recognition of the rapid development of China's telecom industry ...The long-awaited ITU Telecom World 2006 is to open in Hong Kong. It is no doubt that the hosting of this pageant in Hong Kong proves the praise and recognition of the rapid development of China's telecom industry as well as the favor and support to Hong Kong, a world-class trade metropolis. At this opportunity, I'd like to extend my warm congratulations to the event together with readers of China Telecommunications Trade.展开更多
As the core driving force of the new round of informatization development and industrial revolution,the disruptive achievements of artificial intelligence(AI)are rapidly and comprehensively infiltrating into various f...As the core driving force of the new round of informatization development and industrial revolution,the disruptive achievements of artificial intelligence(AI)are rapidly and comprehensively infiltrating into various fields of human activities.Although technologies and applications of AI have been widely studied and factors that affect AI adoption are identified in existing literature,the impact of success factors on AI adoption remains unknown.Accordingly,this paper proposes a framework to explore the impacts of success factors on AI adoption in telecom industry by integrating the technology,organization,and environment(TOE)framework and diffusion of innovation(DOI)theory.Particularly,this framework consists of factors regarding external environment,organizational capabilities,and innovation attributes of AI.The framework is empirically tested with data collected by surveying telecom companies in China.Structural equation modeling is applied to analyze the data.The study provides support for firms’decision-making and resource allocation regarding AI adoption.展开更多
Telecom enterprises are in urgent need of a large amount of funds forupdating networks and expanding market shares, while asset-backed Securitization is the most rapidlyand vigorously growing product of financial inno...Telecom enterprises are in urgent need of a large amount of funds forupdating networks and expanding market shares, while asset-backed Securitization is the most rapidlyand vigorously growing product of financial innovation in the international capital market. Sincetelecom asset is characterized by long recovery period, poor liquidity, high quality and stable cashflow, which are the basic conditions for using asset-backed Securitization to finance, asset-backedSecuritization can be a new financing way for telecom enterprises.展开更多
The proliferation of internet communication channels has increased telecom fraud,causing billions of euros in losses for customers and the industry each year.Fraudsters constantly find new ways to engage in illegal ac...The proliferation of internet communication channels has increased telecom fraud,causing billions of euros in losses for customers and the industry each year.Fraudsters constantly find new ways to engage in illegal activity on the network.To reduce these losses,a new fraud detection approach is required.Telecom fraud detection involves identifying a small number of fraudulent calls from a vast amount of call traffic.Developing an effective strategy to combat fraud has become challenging.Although much effort has been made to detect fraud,most existing methods are designed for batch processing,not real-time detection.To solve this problem,we propose an online fraud detection model using a Neural Factorization Autoencoder(NFA),which analyzes customer calling patterns to detect fraudulent calls.The model employs Neural Factorization Machines(NFM)and an Autoencoder(AE)to model calling patterns and a memory module to adapt to changing customer behaviour.We evaluate our approach on a large dataset of real-world call detail records and compare it with several state-of-the-art methods.Our results show that our approach outperforms the baselines,with an AUC of 91.06%,a TPR of 91.89%,an FPR of 14.76%,and an F1-score of 95.45%.These results demonstrate the effectiveness of our approach in detecting fraud in real-time and suggest that it can be a valuable tool for preventing fraud in telecommunications networks.展开更多
文摘With never-ending changes and improvements and an increasing industrial scale of the Internet, the emerging new application trends, such as social networking, network video, intelligent search and mobile Internet, and new Internet technologies, such as Mashup, artificial intelligence, grid computing and open platform, are significantly influencing the Internet industrial structure. Moreover, the rapid development of the Internet and the convergence of the Internet and telecom networks, especially the development of mobile Internet, are giving the telecom industry a shock. This shock will certainly change the structure of the telecom industry, gradually break the monopoly status of telecom operators, shift the telecom emphasis to services and contents, and enhance the importance of terminal vendors in the industrial chain.
文摘The long-awaited ITU Telecom World 2006 is to open in Hong Kong. It is no doubt that the hosting of this pageant in Hong Kong proves the praise and recognition of the rapid development of China's telecom industry as well as the favor and support to Hong Kong, a world-class trade metropolis. At this opportunity, I'd like to extend my warm congratulations to the event together with readers of China Telecommunications Trade.
文摘As the core driving force of the new round of informatization development and industrial revolution,the disruptive achievements of artificial intelligence(AI)are rapidly and comprehensively infiltrating into various fields of human activities.Although technologies and applications of AI have been widely studied and factors that affect AI adoption are identified in existing literature,the impact of success factors on AI adoption remains unknown.Accordingly,this paper proposes a framework to explore the impacts of success factors on AI adoption in telecom industry by integrating the technology,organization,and environment(TOE)framework and diffusion of innovation(DOI)theory.Particularly,this framework consists of factors regarding external environment,organizational capabilities,and innovation attributes of AI.The framework is empirically tested with data collected by surveying telecom companies in China.Structural equation modeling is applied to analyze the data.The study provides support for firms’decision-making and resource allocation regarding AI adoption.
文摘Telecom enterprises are in urgent need of a large amount of funds forupdating networks and expanding market shares, while asset-backed Securitization is the most rapidlyand vigorously growing product of financial innovation in the international capital market. Sincetelecom asset is characterized by long recovery period, poor liquidity, high quality and stable cashflow, which are the basic conditions for using asset-backed Securitization to finance, asset-backedSecuritization can be a new financing way for telecom enterprises.
基金This research work has been conducted in cooperation with members of DETSI project supported by BPI France and Pays de Loire and Auvergne Rhone Alpes.
文摘The proliferation of internet communication channels has increased telecom fraud,causing billions of euros in losses for customers and the industry each year.Fraudsters constantly find new ways to engage in illegal activity on the network.To reduce these losses,a new fraud detection approach is required.Telecom fraud detection involves identifying a small number of fraudulent calls from a vast amount of call traffic.Developing an effective strategy to combat fraud has become challenging.Although much effort has been made to detect fraud,most existing methods are designed for batch processing,not real-time detection.To solve this problem,we propose an online fraud detection model using a Neural Factorization Autoencoder(NFA),which analyzes customer calling patterns to detect fraudulent calls.The model employs Neural Factorization Machines(NFM)and an Autoencoder(AE)to model calling patterns and a memory module to adapt to changing customer behaviour.We evaluate our approach on a large dataset of real-world call detail records and compare it with several state-of-the-art methods.Our results show that our approach outperforms the baselines,with an AUC of 91.06%,a TPR of 91.89%,an FPR of 14.76%,and an F1-score of 95.45%.These results demonstrate the effectiveness of our approach in detecting fraud in real-time and suggest that it can be a valuable tool for preventing fraud in telecommunications networks.
