Research on the Construction of an Interactive Design Platform Based on Neural Networks and Precision Push Algorithms
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| Publicado en: | International Journal of Cognitive Informatics & Natural Intelligence. vol. 19, no. 1 (2025), p. 1-22 |
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| Autor principal: | |
| Publicado: |
IGI Global
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| Materias: | |
| Acceso en línea: | Citation/Abstract Full Text - PDF |
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|---|---|---|---|
| 001 | 3230103065 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 1557-3958 | ||
| 022 | |a 1557-3966 | ||
| 024 | 7 | |a 10.4018/IJCINI.383949 |2 doi | |
| 035 | |a 3230103065 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 100 | 1 | |a Wang, Yujie |u Henan Institute of Economics and Trade, China | |
| 245 | 1 | |a Research on the Construction of an Interactive Design Platform Based on Neural Networks and Precision Push Algorithms | |
| 260 | |b IGI Global |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a With the development of the internet, virtual interactive design platforms have gradually emerged. Traditional information carriers have shifted from text and images to multimedia content such as audio and video, and the popularity of social networks has driven new changes in the construction of media platforms. More and more platforms are user-centered, combining big data analysis and personalized recommendations to generate video push systems. This paper uses neural network algorithms to study the construction of interactive design platforms and accurate content pushing. It discusses the information processing issues in interactive design and the reasons behind the popularity of platform-based content push. By utilizing big data analysis and user-centered functions, a video interactive design platform was built, enhancing the visual design effect. The research shows that neural network algorithms can effectively improve the visual design of the platform and provide users with more accurate content recommendations. | |
| 653 | |a Augmented reality | ||
| 653 | |a Accuracy | ||
| 653 | |a User behavior | ||
| 653 | |a Data processing | ||
| 653 | |a Collaboration | ||
| 653 | |a Big Data | ||
| 653 | |a Social networks | ||
| 653 | |a Algorithms | ||
| 653 | |a Data analysis | ||
| 653 | |a Visual effects | ||
| 653 | |a Cognition & reasoning | ||
| 653 | |a Wireless networks | ||
| 653 | |a Design optimization | ||
| 653 | |a Social organization | ||
| 653 | |a Video industry | ||
| 653 | |a Neural networks | ||
| 653 | |a Virtual reality | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Genetic algorithms | ||
| 653 | |a Information processing | ||
| 653 | |a Data collection | ||
| 653 | |a Informatics | ||
| 773 | 0 | |t International Journal of Cognitive Informatics & Natural Intelligence. |g vol. 19, no. 1 (2025), p. 1-22 | |
| 786 | 0 | |d ProQuest |t Biological Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3230103065/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3230103065/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |