The Application of Intelligent Technology in Computer Information Systems
Keywords:
Intelligent technology, Computer information systems, ApplicationAbstract
The application of intelligent technology in computer information systems has demonstrated enormous potential and value. Based on this, this article briefly introduces the overview of computer information systems, analyzes the core elements of intelligent technology, and discusses the application of intelligent technology in computer information systems, including the application of intelligent decision support systems, intelligent customer service systems, intelligent monitoring systems, intelligent recommendation systems, intelligent operation and maintenance management systems, etc. These applications not only promote the intelligent upgrading of computer information systems, but also inject new vitality and momentum into the development of various industries.
References
Deng, X., & Yang, J. (2025, August). Multi-Layer Defense Strategies and Privacy Preserving Enhancements for Membership Reasoning Attacks in a Federated Learning Framework. In 2025 5th International Conference on Computer Science and Blockchain (CCSB) (pp. 278-282). IEEE.
Sultan, N., Patwar, N., Wei, X., Chew, J., Liu, J., & Du, R. (2026). FedGuard: A Robust Federated AI Framework for Privacy-Conscious Collaborative AML, Inspired by DARPA GARD Principles. International Academic Journal of Social Science, 2, 1–16. https://doi.org/10.5281/zenodo.18253151
Zhu, Y., Yu, W., & Li, R. (2025). SAGCN: A spatiotemporal attention-weighted graph convolutional network with IoT integration for adolescent tennis motion analysis. Alexandria Engineering Journal, 128, 652-662.
Yang, Y. (2025). Research on Site Reliability Optimization Technology Based on Synthetic Monitoring in Cloud Environments.
Zhang, X. (2024). Research on Dynamic Adaptation of Supply and Demand of Power Emergency Materials based on Cohesive Hierarchical Clustering. Innovation & Technology Advances, 2(2), 59–75. https://doi.org/10.61187/ita.v2i2.135
Zhou, J., & Cen, W. (2024). Investigating the Effect of ChatGPT-like New Generation AI Technology on User Entrepreneurial Activities. Innovation & Technology Advances, 2(2), 1–20. https://doi.org/10.61187/ita.v2i2.124
Tang, Z., Feng, Y., Zhang, J., & Wang, Z. (2026). SVD-BDRL: A trustworthy autonomous driving decision framework based on sparse voxels and blockchain enhancement. Alexandria Engineering Journal, 134, 433-446.
Lu, K., Sui, Q., Chen, X., & Wang, Z. (2025). NeuroDiff3D: a 3D generation method optimizing viewpoint consistency through diffusion modeling. Scientific Reports, 15(1), 41084.
Xie, J., Zhang, L., Cheng, L., Yao, J., Qian, P., Zhu, B., & Liu, G. (2025). MARNet: Multi-scale adaptive relational network for robust point cloud completion via cross-modal fusion. Information Fusion, 103505.
Q. Tian, D. Zou, Y. Han and X. Li, "A Business Intelligence Innovative Approach to Ad Recall: Cross-Attention Multi-Task Learning for Digital Advertising," 2025 IEEE 6th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT), Shenzhen, China, 2025, pp. 1249-1253, doi: 10.1109/AINIT65432.2025.11035473.
Hsu, Hsin-Ling, et al. "MEDPLAN: A Two-Stage RAG-Based System for Personalized Medical Plan Generation." arXiv preprint arXiv:2503.17900 (2025).
Ding, Cheng, et al. "Deep learning for personalized electrocardiogram diagnosis: A review." arXiv preprint arXiv:2409.07975 (2024).
Yuan, Y., & Xue, H. (2025). Cross-Media Data Fusion and Intelligent Analytics Framework for Comprehensive Information Extraction and Value Mining.
Yuan Y, Xue H. Multimodal Information Integration and Retrieval Framework Based on Graph Neural Networks[C]//Proceedings of the 2025 4th International Conference on Big Data, Information and Computer Network. 2025: 135-139.
Li Z, Ji Q, Ling X, et al. A comprehensive review of multi-agent reinforcement learning in video games[J]. Authorea Preprints, 2025.
Zhang, Z., Wang, J., Li, Z., Wang, Y., & Zheng, J. (2025). Anncoder: A mti-agent-based code generation and optimization model. Symmetry, 17(7), 1087.
Wang, Q., Li, Y., & Myers, B. A. (2023). Designing AI-powered interactive systems with large language models. Communications of the ACM, 66(9), 78–87.
Sha F, Meng J, Zheng X, et al. Sustainability Under Fire: How China-US Tensions Impact Corporate ESG Performance? [J]. Finance Research Letters, 2025: 107882.
Sha F, Ding C, Zheng X, et al. Weathering the Policy Storm: How Trade Uncertainty Shapes Firm Financial Performance through Innovation and Operations[J]. International Review of Economics & Finance, 2025: 104274.
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