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Mapping the Landscape of Machine Learning Research through Clustering

Students & Supervisors

Student Authors
Md. Rawha Siddiqi Riad
Bachelor of Science in Computer Science & Engineering, FST
Sharier Mahmud Akash
Bachelor of Science in Computer Science & Engineering, FST
Md. Nuruzzaman
Bachelor of Science in Computer Science & Engineering, FST
Supervisors
Dr. Abdus Salam
Associate Professor, Faculty, FST

Abstract

This paper explores a data-driven approach to analyze research trends in the machine learning (ML) domain. The main objectives are to identify the subdomains within the ML domain and to find their popularity over time. A dataset of 10,000 research papers (collected by web scraping) from arXiv was used, containing titles, abstracts and dates related to ML. The text data were processed using TF–IDF vectorization and reduced through Principal Component Analysis (PCA) before applying K–Means clustering to group similar papers. A predetermined set of keywords is used to automatically label each cluster. It helps to identify machine learning subdomains, including deep learning, computer vision, reinforcement learning, and natural language processing. In addition, trend analysis and visualizations were performed to examine changes in research focus from 2021 to 2025. The results show that Time Series and Forecasting has become the most popular and fastest growing area. At the same time, traditional fields like Optimization and Computer Vision continue to remain important. This research shows that text based data science methods can effectively analyze the research trend in ML.

Keywords

research trends text clustering TF-IDF PCA K-Means sub-domain labeling topic modeling

Publication Details

  • Type of Publication:
  • Conference Name: 2026 IEEE 2nd International Conference on Quantum Photonics, Artificial Intelligence & Networking
  • Date of Conference: 16/04/2026 - 16/04/2026
  • Venue: IT Business Incubator, Chittagong University of Engineering and Technology (CUET), Chattogram, Bangladesh
  • Organizer: IEEE Photonics Society Bangladesh Chapter
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