Elisei, Pietro and Golubovic-Matic, Darinka and Laconte, Pierre and Popovich, Vasily and Popovich, Tatiana and Schrenk, Manfred and Shutkov, Vladimir and Zagvozdkin, Artem (2023) Intelligent Social Network. 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, Regional Planning and Information Society. pp. 439-444. ISSN 2521-3938
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Text (Intelligent Social Network)
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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.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Intelligent Social Network, Artificial Intelligence, Inference Machine, Ontology, Scenario Approach |
| Subjects: | H Social Sciences > HM Sociology Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) |
| Depositing User: | REAL CORP Administrator |
| Date Deposited: | 02 Oct 2023 18:30 |
| Last Modified: | 04 Oct 2023 17:47 |
| URI: | http://repository.corp.at/id/eprint/977 |
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