With the recent advances of the Internet of Things, and the increasing accessibility of 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 relationship 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 relationship explosion problem. This paper discusses the role of IoT in social relationships detection and 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.
翻译:近十年来,随着物联网的最近发展,随着无处不在的计算机资源和移动装置的日益普及、丰富的媒体内容的普及以及随之而来的社会、经济和文化变革,计算机技术和应用在过去十年中迅速发展,现在它们超越了个人计算,促进协作和一般社会互动,导致IoT实体之间的社会关系迅速扩散,这些关系及其不同的社会特点导致计算和通信瓶颈,使IoT网络无法利用这些关系改进所提供的服务和定制交付的内容,即所谓的关系爆炸。另一方面,在社会计算中人工智能应用的快速进步导致出现了一个有希望的研究领域,即人工社会情报,有可能解决社会关系爆炸问题。本文讨论了IoT在社会关系探测和管理中的作用,IoT的社会关系爆炸问题,并审查了使用ASI的拟议解决办法,包括面向社会的机构学习和深层次学习技术。