An Exploration of the Development of Computerized Data Mining Techniques and Their Application
DOI:
https://doi.org/10.62051/ijcsit.v3n1.26Keywords:
Computer, Data mining, Data processing, Technology applicationAbstract
The process of data mining involves extracting valuable information and knowledge from vast amounts of data, encompassing various fields such as statistics, machine learning, and database theory. It transcends mere data processing tools, employing intelligent methods for data analysis and stands as a pivotal technology in the era of big data. Its applications span across numerous domains including consumer behavior analysis, market marketing strategies, risk management, medical diagnosis, and fraud detection, with notable prominence in the realm of commerce. In e-commerce platforms, data mining techniques adeptly analyze user purchase histories and browsing records to precisely identify user preferences, recommend personalized products, thus enhancing user satisfaction and sales revenue. In devising marketing strategies, analyzing market data and consumer feedback optimizes product promotion strategies, bolstering market competitiveness. In the medical domain, data mining exhibits robust vitality. By analyzing patient medical records, genetic data, drug response data, predictions of disease trends, optimization of treatment plans, and even early disease warnings are made possible, thereby improving disease cure rates. In the realm of financial security, data mining plays a pivotal role by analyzing transaction data and user behavior to timely detect abnormal transactions and identify fraudulent activities, thereby safeguarding the security and stability of the financial system. In the Internet of Things (IoT) domain, data mining techniques analyze massive sensor data, enabling real-time monitoring and predictive maintenance of devices, thus enhancing operational efficiency and longevity. Data mining extends beyond the aforementioned domains, finding significant applications in social governance, scientific research, intelligent manufacturing, and more. Not only does data mining enhance the scientific rigor and precision of decision-making, but it also empowers various industries to improve efficiency, realize intelligent transformations, thereby further advancing societal progress.
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References
Sarswat K P, Singh S R, Pathapati H S V S. Real time electronic-waste classification algorithms using the computer vision based on Convolutional Neural Network (CNN): Enhanced environmental incentives [J]. Resources, Conservation Recycling, 2024, 207107651.
Ros F, Riad R. DLCS: A deep learning-based Clustering solution without any clustering algorithm, Utopia? [J]. Knowledge-Based Systems, 2024, 296111834.
Songyang L. Simulation of association rule mining based on sensor networks in Chinese language learning recommendation system for college students [J]. Measurement: Sensors, 2024, 33101208.
Guoming J. Artificial intelligence-based adaptive anomaly detection technology for IaaS cloud virtual machines [J]. Journal of Engineering and Applied Science, 2024, 71(1):11.
GeethaRamani R, Balasubramanian L. Retinal blood vessel segmentation employing image processing and data mining techniques for computerized retinal image analysis [J]. Biocybernetics and Biomedical Engineering, 2016, 36(1):102-118.
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