Syed Tangim Pasha
- Collaborator, HCI Wing
Lecturer
Department of Computing and Information System
Daffodil International University
Research Interests
Health Informatics, Affective Computing, Digital Health, Wearable Computing
Conference Paper2023Cited by 5
Genre Classification of Bangla Poem Using Machine Learning and Deep Learning Techniques
Syed Tangim Pasha, Ashraful Islam, Mohammed Masudur Rahman, Eshtiak Ahmed, Md Ferdouse Ahmed Foysal, Md Zahangir Alam
2023 IEEE World AI IoT Congress (AIIoT)
IEEE, pp. 0236–0242
Abstract
The computational analysis of the Bangla poems is a challenging task due to the diverse linguistic, stylistic, and semantic features of the Bangla language. In this work, we prepared a dataset of 1311 Bangla poems of two separate categories: Love and Miscellaneous poem, which contain 500 and 811 poems respectively. We used word or semantic-based features to classify Bangla poems using the TF-IDF feature techniques. We used Logistic Regression, Naïve Bayes (NB), and Support Vector Machine (SVM) models for classification through machine learning, and we used Bayesian optimization techniques for hyperparameters tuning of these three models. We also used LSTM, CNN, and transformer models for this research. For the performance evaluation of the classification models, we used four evaluation metrics of precision, recall, F1-score, and accuracy. We also used the ROC-AUC curve to distinguish between all the machine learning and deep learning models. The experimental results expressed that, the transformer model achieved the highest accuracy compared to all the typical machine learning and deep learning models with an accuracy of 87%.
Keywords
Artificial intelligenceBengaliComputer scienceSupport vector machineMachine learningHyperparameterNatural language processingNaive Bayes classifierDeep learningTransformer
CCDS Authors
Ashraful Islam, PhD
- Center Director, CCDS
- Director, HCI Wing
Assistant Professor
Department of Computer Science and Engineering
Independent University, Bangladesh (IUB)Research Interests
Human-Computer Interaction, AI for Social Good, AI for Public Health, AI for Impact
Eshtiak Ahmed
- Collaborator, HCI Wing
Doctoral Researcher
Gamification Group
Tampere University, Finland
Research Interests
Human-Computer Interaction, Human-Robot Interaction, Gamification and Assistive Technologies
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Cited By
- 1.Rayhanuzzaman, Tanjim Mahmud, Utpol Kanti Das, Sultana Rokeya Naher, Mohammad Shahadat Hossain, Karl Andersson. (2024). Investigating the Effectiveness of Deep Learning and Machine Learning for Bangla Poems Genre Classification. , 1–6[10.1109/conit61985.2024.10627555]
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- 3.Danish Haikal Bin Suhaimi, Hasiah Mohamed, Nurul Izzah Irdina Binti Mohd Kairudin, Syarifah Bahiyah Rahayu. (2025). Malay Pantun Theme Classification Using Support Vector Machine. , 324–329[10.1109/icset65917.2025.11283995]
- 4.Bikokhita Dutta, Mandira Neog, Nomi Baruah. (2024). Unveilling the Effectiveness of LSTM with TF-IDF in Assamese Poem Classification:A Comparative Analysis with Conventional and Deep Learning Approaches. , 1–6[10.1109/icccnt61001.2024.10725384]
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