Study on artificial intelligence: The state of the art and future prospects

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 infi...

https://www.tandfonline.com/doi/pdf/10.1080/23270012.2020.1852895

Explore success factors that impact artificial intelligence adoption on telecom industry in China

Information Communication and Computation Technology (ICCT) also called as Digital Technology and is considered as a general purpose universal technology due to its ability to solve many problems in the human society related to basic needs, advanced wants, and dreamy desires. In this chapter, initially, we have identified various quality attributes of Digital Service and some prominent published works in digital service innovation. The important underlying technologies of ICCT which are emerging as technologies of 21st century including Artificial intelligence& robotics, Big data & business analytics, Cloud computing& storage, Digital marketing, 3D printing, Internet of Things, Online ubiquitous education, Quantum computing, Information storage technology, and Virtual & Augmented Reality are considered for possible innovations in such industries. The applications of ICCT underlying technologies in some of the prominent service industry sectors are identified and the management of ICCT underlying technology usage strategies for digital service innovation in tertiary sector industries are analysed.

/pdf/management-of-icct-underlying-technologies-used-for-digital-yv5edwfh9y.pdf

Management of ICCT underlying Technologies used for Digital Service Innovation

Acquisition and the retention of customers are the top most concerns in today's business world. The rapid increase of market in every business is leading to higher subscriber base. Consequently, companies have realized the importance of retaining the on hand customers. It has become mandatory for the service providers to reduce churn rate because the negligence could be resulted as profitability reduction in major perspective. Churn prediction helps in identifying those customers who are likely to leave a company. Telecommunication is coping with the issue of ever increasing churn rate. Data mining techniques enable these telecommunication companies to be equipped with effective methods for reducing churn rate. The paper reviews 61 journal articles to survey the pros and cons of renowned data mining techniques used to build predictive customer churn models in the field of telecommunication and thus providing a roadmap to researchers for knowledge accumulation about data mining techniques in telecom.

/pdf/customer-churn-prediction-in-telecommunication-a-decade-6cp3zabj3n.pdf

Customer Churn Prediction in Telecommunication A Decade Review and Classification

BackgroundA high burden of non-communicable diseases (NCDs) is contributing to high mortality and morbidity in India. Recent advancements in digital health interventions, including mHealth, eHealth...

https://journals.sagepub.com/doi/pdf/10.1177/2055207619896153

Digital interventions for people living with non-communicable diseases in India: A systematic review of intervention studies and recommendations for future research and development

Artificial intelligence (AI) has been applied to the telecommunications industry for more than a decade. The purpose of this paper is to examine the application of AI in the telecommunications industry sector. Our research finds that AI's first main application in telecommunications is in the network management area. Expert systems and machine learning are the two AI techniques that have been widely used in telecommunications, while machine learning and distributed artificial intelligence are the two AI techniques which are most promising for the future. The research also finds that different AI techniques have their unique applications in the telecommunications industry.

Artificial intelligence applications in the telecommunications industry

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Artificial intelligence applications in the telecommunications industry