Abstract
The papers in this special section focus on emerging computational intelligence (CI) based theories and methodologies for big graph data management. The emerging CI techniques cover a broad range of nature-inspired, multidisciplinary computational methodologies, such as fuzzy logic, graph pattern matching, graph neural networks, graph embedding, graph attention, evolutionary computing, cognitive computing, learning theory, and probabilistic methods. The objective of this special issue is to explore how CI models and their variants can be adapted, augmented and extended to deal with applications involving very large scale graph data.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEE Transactions on Emerging Topics in Computational Intelligence
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
