In this era of information explosion, data are commonly incomplete in many big-data-related applications such as e-commerce systems, environmental monitoring systems, wireless sensor networks, and social networks, as the related information or relationships are unlikely to be fully observed or collected in practice. Although some information is missing from incomplete data, they still contain rich latent knowledge and patterns, e.g., users’ potential preferences on items in e-commerce systems. Hence, how to efficiently and effectively filter valuable knowledge and patterns out of incomplete big data (IBD) has become a significant challenge.
The human brain is the most intelligent biological computing ‘machine’ at a fundamental level. Against this backdrop, neuroscience-inspired intelligent computing, like artificial neural network (ANN) has made dramatic advances in the last decades. It has been increasingly applied to a range of practical problems, such as natural language processing, visual analysis, speech recognition, robot control, language translation, etc. It plays a crucial role in promoting the rapid development of science and technology.
To expand knowledge of incomplete big data analysis and to educate students and researchers on the fundamentals of this area, we’ve invited Prof. Di Wu from Chinese Academy of Sciences, China, along with Dr. Zhong Chen from Xavier University of Louisiana, USA, and Dr. Dianlong You from Yanshan University, China, to work on a Special Issue on Incomplete Big Data Analysis Based on Neuroscience-Inspired Intelligent Computing
This special issue will be included in the Journal of Computational and Cognitive Engineering (JCCE) to shed light on the recent advancements in big data and provide experts with insights into the improvement of human life and the environment
"This Special Issue aims at exploring the latest up-to-date theory, methods, and applications regarding IBD analysis based on neuroscience-inspired intelligent computing" said by Prof. Di Wu.
Paper submission begins from 01 December 2022 and end by 30 June 2023. The topics of interest include, but are not limited to, the following:
· Brain-like computing based IBD analysis
· Cognitive computing based IBD analysis
· IBD Representation learning with neuroscience
· Intelligent robots and systems for IBD analysis
· Human-Machine systems for IBD analysis
· Information security with neuroscience for IBD analysis
· Human-Centric Computing for IBD analysis
For more information about this special issue, you can visit the journal