Cognitive Services Integrating with Big Data, Clouds and IoT
A special issue of Big Data and Cognitive Computing (ISSN 2504-2289).
Deadline for manuscript submissions: closed (31 March 2018) | Viewed by 18375
Special Issue Editors
Interests: blockchain systems; telecommunication networks information systems personal communications networking cloud and edge computing
Special Issues, Collections and Topics in MDPI journals
Interests: body area networks; Internet of Things; agent-based computing
Special Issues, Collections and Topics in MDPI journals
Interests: mobile computing; edge intelligence; cognitive wireless communications
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In the past decade, the computer and information industry has experienced rapid changes, in both the platform scale and the scope of applications. Computers, smart phones, clouds, and social networks demand, not only high performance, but also a high degree of machine intelligence. In fact, we are entering an era of big data analysis and cognitive computing. This trendy movement is observed by the pervasive use of mobile phones, storage and computing clouds, the revival of artificial intelligence in practice, extended supercomputer applications, and wide spread deployment of Internet of Things (IoT) platforms. To face these new computing and communication paradigms, we must upgrade the cloud and IoT ecosystems with new capabilities, such as machine learning, IoT sensing, and data analytics that can provide humans with cognitive services.
In the big data era, successful cloud systems, web services, and datacenters must be designed to store, process, learn, and analyze big data to discover new knowledge or make critical decisions. The purpose is to build up a big data industry to provide cognitive services to offset human shortcomings in handling labor-intensive tasks with high efficiency. These goals are achieved through hardware virtualization, machine learning, deep learning, IoT sensing, data analytics, and cognitive computing. For example, new cloud services have appeared, such as Learning as a Services (LaaS), Analytics as a Service (AaaS), or Security as a Service (SaaS), along with the growing practices of machine learning and data analytics.
Prof. Dr. Victor C.M. Leung
Dr. Yin Zhang
Dr. Giancarlo Fortino
Guest Editors
Manuscript Submission Information
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Keywords
- Novel architecture and infrastructure for cognitive services
- Multi-modal fusion for cognitive services
- Contextual data management and mining platforms
- Cognitive computing, affective computing, machine learning
- Intelligent, cognitive and interactive interface
- Privacy protected discovery and adaptation in cognitive services
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