Development of an AutoML Web Platform for Text Classification Automation 


Vol. 13,  No. 10, pp. 537-544, Oct.  2024
https://doi.org/10.3745/TKIPS.2024.13.10.537


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  Abstract

The rapid advancement of artificial intelligence and machine learning technologies is driving innovation across various industries, with natural language processing offering substantial opportunities for the analysis and processing of text data. The development of effective text classification models requires several complex stages, including data exploration, preprocessing, feature extraction, model selection, hyperparameter optimization, and performance evaluation, all of which demand significant time and domain expertise. Automated machine learning (AutoML) aims to automate these processes, thus allowing practitioners without specialized knowledge to develop high-performance models efficiently. However, current AutoML frameworks are primarily designed for structured data, which presents challenges for unstructured text data, as manual intervention is often required for preprocessing and feature extraction. To address these limitations, this study proposes a web-based AutoML platform that automates text preprocessing, word embedding, model training, and evaluation. The proposed platform substantially enhances the efficiency of text classification workflows by enabling users to upload text data, automatically generate the optimal ML model, and visually present performance metrics. Experimental results across multiple text classification datasets indicate that the proposed platform achieves high levels of accuracy and precision, with particularly notable performance when utilizing a Stacked Ensemble approach. This study highlights the potential for non-experts to effectively analyze and leverage text data through automated text classification and outlines future directions to further enhance performance by integrating Large language models.

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[IEEE Style]

H. Song, J. Kang, B. Park, J. Kim, K. Jeon, J. Yoon, H. Chung, "Development of an AutoML Web Platform for Text Classification Automation," The Transactions of the Korea Information Processing Society, vol. 13, no. 10, pp. 537-544, 2024. DOI: https://doi.org/10.3745/TKIPS.2024.13.10.537.

[ACM Style]

Ha-Yoon Song, Jeon-Seong Kang, Beom-Joon Park, Junyoung Kim, Kwang-Woo Jeon, Junwon Yoon, and Hyun-Joon Chung. 2024. Development of an AutoML Web Platform for Text Classification Automation. The Transactions of the Korea Information Processing Society, 13, 10, (2024), 537-544. DOI: https://doi.org/10.3745/TKIPS.2024.13.10.537.

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