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International Journal of Intelligent Data and Machine Learning

Open Access Peer Review International
Open Access

A Comprehensive Framework for Intelligent Data Analytics in Modern Intelligent Systems: Design, Methods, and Applications

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Dr. Oliver Henry Mitchell 1 ,
4 Department of Data Science, University College London, London, UK

Abstract

The rapid expansion of intelligent systems across domains such as healthcare, finance, social media analytics, and enterprise automation has intensified the demand for adaptive and scalable data analysis architectures. Traditional static machine learning pipelines are increasingly inadequate for handling high-velocity, heterogeneous, and context-sensitive data streams. This research proposes an adaptive machine learning–driven architecture designed to optimize data analysis in complex intelligent systems by integrating dynamic model selection, contextual feature learning, and hierarchical fusion mechanisms.

The study synthesizes advancements in sequential learning, multimodal intelligence, graph-based prediction systems, and contextual embeddings to construct a unified adaptive framework. Drawing upon recent developments in sentiment analysis, temporal graph neural networks, and large-scale data intelligence systems, the proposed architecture emphasizes real-time adaptability, self-optimization, and domain-aware learning capabilities.

The findings indicate that adaptive architectures significantly improve predictive accuracy, computational efficiency, and scalability in complex environments compared to conventional static systems. Additionally, the integration of contextual intelligence mechanisms—aligned with emerging industry trends toward generative AI adoption in analytics ecosystems—demonstrates improved robustness in dynamic data environments. The research further highlights critical challenges such as model drift, computational overhead, and ethical considerations in AI-driven decision systems.

Keywords

Adaptive machine learning, intelligent systems, data analysis architecture

References

AI for Sales and Marketing Market worth $240.58 billion by 2030. [Electronic resource] Access mode: https://www.marketsandmarkets.com/PressReleases/ai-for-sales-and-marketing.asp (date accessed: 01.07.2025).
Alshattnawi S. et al. Beyond word-based model embeddings: Contextualized representations for enhanced social media spam detection //Applied Sciences. –2024. –Vol. 14 (6). –pp. 1-25. https://doi.org/10.3390/app14062254.
Chan J. Y. L. et al. State of the art: a review of sentiment analysis based on sequential transfer learning //Artificial Intelligence Review. –2023. –Vol. 56 (1). –pp. 749-780.
Gartner Predicts 75% of Analytics Content to Use GenAI for Enhanced Contextual Intelligence by 2027. [Electronic resource] Access mode: https://www.gartner.com/en/newsroom/press-releases/2025-06-18-gartner-predicts-75-percent-of-analytics-content-to-use-genai-for-enhanced-contextual-intelligence-by-2027 (accessed: 06/25/2025).
Giovanola B., Granata P. Ethics for human-centered education in the age of AI //Entrepreneurship and Digital Humanities. –Edward Elgar Publishing, 2024. –pp. 96-109.
Jin R., Liu X., Murata T. Predicting popularity trend in social media networks with multi-layertemporal graph neural networks //Complex & Intelligent Systems. –2024. –Vol. 10 (4). –pp. 4713-4729.
Meltwater; We Are Social. Digital 2024: Global Overview Report. [Electronic resource] Access mode: https://datareportal.com/reports/digital-2024-global-overview-report (date accessed: 17.06.2025).
Musliadi K. H., Zainuddin H., Wabula Y. Twitter social media conversion topic trending analysis using latent Dirichlet allocation algorithm //Journal of Applied Engineering and Technological Science (JAETS). –2022. –Vol. 4 (1). –pp. 390-399.
Pandey R. et al. Hybrid attention-based long short-term memory network for sarcasm identification //Applied Soft Computing. –2021. –Vol. 106. https://doi.org/10.1016/j.asoc.2021.107348.
Rangu, S. (2025). Analyzing the impact of AI-powered call center automation on operational efficiency in healthcare. Journal of Information Systems Engineering and Management, 10(45s), 666–689. https://doi.org/10.55278/jisem.2025.10.45s.666
Sardana, J., & Mukesh Reddy Dhanagari. (2025). Bridging IoT and Healthcare: Secure, Real-Time Data Exchange with Aerospike and Salesforce Marketing Cloud. International Journal of Computational and Experimental Science and Engineering, 11(3). https://doi.org/10.22399/ijcesen.385313.
Samantapudi, R. K. R. (2025). Advantages & impact of fine tuning large language models for ecommerce search. Journal of Information Systems Engineering and Management, 10(45s), 600–622. https://doi.org/10.52783/jisem.v10i45s.8898
Srilatha, S. (2025). Integrating AI into enterprise content management systems: A roadmap for intelligent automation. Journal of Information Systems Engineering and Management, 10(45s), 672–688. https://doi.org/10.52783/jisem.v10i45s.8904
Talkwalker. Social Media Trends Report 2024. [Electronic resource] Access mode: https://www.talkwalker.com/social-media-trends (date of access: 06/27/2025).
Wang J. et al. Social media popularity prediction with multimodal hierarchical fusion model //Computer Speech & Language. –2023. –Vol. 80. https://doi.org/10.1016/j.csl.2023.101490.
Yue C. A. et al. Public relations meets artificial intelligence: Assessing utilization and outcomes //Journal of Public Relations Research. –2024. –Vol. 36 (6). –pp. 513-534.

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