Embedding GloVe into the corpus using a multi-layer BiLSTM deep learning model for opinion mining through Daraz product reviews

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2022
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In this project, we propose a deep learning approach for opinion mining through product reviews on the online marketplace Daraz. Our method involves embedding GloVe (Global Vectors for Word Representation) into the corpus of product reviews and using a multi-layer bidirectional long short term memory (BiLSTM) model to analyze the sentiment of the reviews. The performance of our model is evaluated using a variety of metrics, including precision, recall, and F1 score. Our results show that our approach is effective at accurately predicting the sentiment of the reviews and outperforms several baseline methods. Overall, our work demonstrates the potential of using deep learning techniques for opinion mining in the context of e-commerce.
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Electrical and Computer Engineering
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North South University
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