Advances in Artificial Intelligence and Machine Learning for Social Networking
A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Big Data and Augmented Intelligence".
Deadline for manuscript submissions: closed (15 November 2022) | Viewed by 346
Special Issue Editors
Interests: information security; machine learning; big data analysis; complex system; IoT; artificial intelligence; social networking
Special Issues, Collections and Topics in MDPI journals
Interests: geometric deep learning; machine learning; network science; social network
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Artificial intelligence, and specifically machine learning, is quickly becoming more pervasive in many fields, with applications ranging from computer science—cybersecurity, hardware design, and human–machine interactions—to social sciences, such as economics, and life sciences, such as biology. The fast diffusion of machine learning was actualized through the efforts of researchers, whose focus is not only on the applications, but also on the development of novel approaches, algorithms, and models, such as geometric deep learning to learn non-Euclidean data.
The focus of this Special Issue is, thus, twofold: to push the state-of-the-art of graph representation learning with novel approaches, while also providing an overview of existing ones, and to promote their application in complex networks, for instance, to tackle hard or large societal impact problems or to gain novel insights using model “explanation” tools. For instance, social networks offer a very important test bench, since they model very large systems with billions of people interacting with each other in nontrivial ways. In this context, designing novel tools allowing for the study of the evolution of a system while learning a given problem, and to explain the underlying dynamics, may even offer a new perspective on the system and the problem itself.
In summary, this Special Issue aims to discuss and cover trending topics, such as the application of data science and network science and geometric deep learning to socially relevant problems (e.g., cybersecurity, healthcare, biology, economics, and social sciences).
Prof. Michele Malgeri
Dr. Marco Grassia
Guest Editors
Manuscript Submission Information
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Keywords
- machine and deep learning network science data science artificial intelligence network representation graph embedding complex networks social networks graph representation learning geometric deep learning
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