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Student Project | Computer Technology | Volume 14 Issue 4, April 2025 | Pages: 1560 - 1564 | India
Emotion Correlation Mining Through Deep Learning
Abstract: In this project, we present a hybrid model adopting deep-learning techniques for sentiment categorization and emotion correlation mining using RoBERTa and LSTM. The model applies LSTM architectures to learn and predict sequences and to tokenize and embed contextual words with RoBERTa. The intuitive GUI from the model is claimed to improve classification accuracy.
Keywords: Deep Learning, RoBERTa, LSTM, GUI
How to Cite?: Hridhya Das N, Rinsa Rees, "Emotion Correlation Mining Through Deep Learning", Volume 14 Issue 4, April 2025, International Journal of Science and Research (IJSR), Pages: 1560-1564, https://www.ijsr.net/getabstract.php?paperid=SR25416201655, DOI: https://dx.doi.org/10.21275/SR25416201655