Enhancing Thirukkural couplet section classification: a meta-model learning approach

dc.contributor.authorPuvanendran, R
dc.contributor.authorNadarajah, S
dc.contributor.authorParameshwaran, Y
dc.contributor.editorGunawardena, S
dc.date.accessioned2025-11-20T07:37:27Z
dc.date.issued2025
dc.description.abstractThirukkural, a widely translated classical Tamil literary work, is structured into three sections—Arathuppal (virtue), Porutpal (wealth), and Kamathuppal (love). This study proposes a novel meta-model approach to classify Thirukkural couplets, into these sections. In this study, we propose a meta-model approach that integrates various traditional machine learning (ML) algorithms. By leveraging meta-model learning and stacking methodologies, our approach improves classification accuracy and robustness compared to individual models. The results demonstrate the effectiveness of a metamodel learning strategy with TFIDF features in literary text classification.
dc.identifier.conferenceApplied Data Science & Artificial Intelligence (ADScAI) Symposium 2025
dc.identifier.departmentDepartment of Computer Science & Engineering
dc.identifier.doihttps://doi.org/10.31705/ADScAI.2025.41
dc.identifier.emailrukupuvan@gmail.com
dc.identifier.emailsalinada22@gmail.com
dc.identifier.emailyaliniparameswaran2000@gmail.com
dc.identifier.facultyEngineering
dc.identifier.placeMoratuwa, Sri Lanka
dc.identifier.proceedingProceedings of Applied Data Science & Artificial Intelligence Symposium 2025
dc.identifier.urihttps://dl.lib.uom.lk/handle/123/24412
dc.language.isoen
dc.publisherDepartment of Computer Science and Engineering
dc.subjectThirukkural
dc.subjecttext classification
dc.subjectTFTDF
dc.subjectBERT
dc.subjectDistilBERT
dc.subjectmeta-model
dc.subjectmachine learning
dc.titleEnhancing Thirukkural couplet section classification: a meta-model learning approach
dc.typeConference-Extended-Abstract

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