@article{MA1D5A74C,
title = "A Design and Implementation of Automated Classification and Analysis System Using K-Means Clustering for Transition of Database to Micro-Services-Architecture",
journal = "The Journal of Korean Institute of Communications and Information Sciences",
year = "2024",
issn = "1226-4717",
doi = "10.7840/kics.2024.49.9.1306",
author = "Sun-chul Park, Young-han Kim",
keywords = "K-means Clustering, Unsupervised Learning, Cloud Migration, MSA, DBMS Analysis",
abstract = "The most challenging task in transitioning an integrated database to the cloud is categorizing tables according to the structure. We automated this using machine learning clustering, collecting SQL frequencies, generating time-series data, and applying K-Means. We compared the proposed automation method with manual classification, identified K-Means parameters using Elbow, and showed the automation's effectiveness."
}