期刊
IEEE INTERNET OF THINGS JOURNAL
卷 8, 期 24, 页码 17817-17828出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2021.3081556
关键词
Internet of Things; Explosions; Social intelligence; Sensors; Social networking (online); Task analysis; Peer-to-peer computing; Artificial social intelligence (ASI); cyber-physical-social system; Internet of Things (IoT); social IoT (SIoT); social relationships explosion
资金
- National Natural Science Foundation of China [61872038]
With the rapid advancement of IoT and the increase in connectivity, social relationships in the IoT network are rapidly growing, leading to social relationships explosion. However, the emerging field of artificial social intelligence shows promise in addressing this issue.
With the recent advances of the Internet of Things (IoT), and the increasing accessibility to ubiquitous computing resources and mobile devices, the prevalence of rich media contents, and the ensuing social, economic, and cultural changes, computing technology and applications have evolved quickly over the past decade. They now go beyond personal computing, facilitating collaboration and social interactions in general, causing a quick proliferation of social relationships among IoT entities. The increasing number of these relationships and their heterogeneous social features have led to computing and communication bottlenecks that prevent the IoT network from taking advantage of these relationships to improve the offered services and customize the delivered content, known as social relationships explosion. On the other hand, the quick advances in artificial intelligence applications in social computing have led to the emerging of a promising research field known as artificial social intelligence (ASI) that has the potential to tackle the social relationships explosion problem. This article discusses the role of IoT in social relationships management, the problem of social relationships explosion in IoT, and reviews the proposed solutions using ASI, including social-oriented machine-learning and deep-learning techniques.
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