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Intelligent Social Network

Authors: Elisei, Pietro; Golubovic-Matic, Darinka; Laconte, Pierre; Popovich, Vasily; Popovich, Tatiana; Schrenk, Manfred; Shutkov, Vladimir; +1 Authors

Intelligent Social Network

Abstract

Recently emerged social networks are gaining momentum and are becoming an integral part of modern life. The introduction of artificial intelligence methods, such as ChatGPT, show the importance of this field of science in computer technology, science and social life. With more than 20 years of experience in the application of AI methods, we consider it appropriate to share ideas for their application in the interests of everyday human activities. Our main proposal concerns the creation of decision support systems based on social networks, localized in the interests of a particular person. The main technologies that we apply are the following: Scenario Approach, which includes the Ontology System, Inference Machine, a Visual Integrated Development Environment, and a number of mathematical approaches that implement machine learning and DSS. First of all, these are: Singular Value Decomposition and Method of United Randomize Indices. Unlike neural networks, these methods have a clear mathematical interpretation and controlled accuracy. Also for their application there is no need for very large statistics.

LET IT GROW, LET US PLAN, LET IT GROW. Nature-based Solutions for Sustainable Resilient Smart Green and Blue Cities. Proceedings of REAL CORP 2023, 28th International Conference on Urban Development and Regional Planning in the Information Society, 439-444

Country
Austria
Keywords

T Technology (General), Intelligent Social Network, QA76 Computer software, Scenario Approach, Artificial Intelligence, Inference Machine, Ontology, HM Sociology

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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