Challenges and opportunities in big data analytics: Such as the risks and pitfalls of ignoring context/contextualization
This study explores the role of contextualization in big data analytics, emphasizing its significance across various applications including healthcare, urban planning, and network orchestration. The research introduces a novel context-aware recommender system designed to enhance user experience by i...
| Main Author: | |
|---|---|
| Format: | Final Year Project / Dissertation / Thesis |
| Published: |
2024
|
| Subjects: | |
| Online Access: | http://eprints.utar.edu.my/6607/ http://eprints.utar.edu.my/6607/1/fyp_IA_2024_TDCM.pdf |
| Summary: | This study explores the role of contextualization in big data analytics, emphasizing its significance across various applications including healthcare, urban planning, and network orchestration. The research introduces a novel context-aware recommender system designed to enhance user experience by integrating real-time contextual information seamlessly. Through extensive experiments using a Kaggle dataset, the study validates the system’s effectiveness in improving decision-making and operational efficiency. Methodologically, the project employs a comprehensive approach comprising data collection, preprocessing, exploration, and visualization, couple with advance d feature engineering and model evaluation. The findings demonstrates that contextualization significantly increases the precision and relevance of data analysis, there by fostering more informed decision-making. This research not only contributes to the academic discourse on big data but also offers practical insights for organizations aiming to leverage contextual data for strategic advantage. |
|---|