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Zainura Idrus

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Articles

Deep fusion explainable recommendation based on sentiment analysis and feature weighting

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By Kechao Li, Zainura Idrus
| Nature Verified
Abstract Recommendation systems are crucial in helping users search for personalized information. However, the original ratings used by existing recommendation systems can’t accurately represent users’ true rating intentions, ignore sentiment attitudes, and lack explainability. To address this issue, the article proposes the recommendation of Sentiment Analysis and Feature Weighting (SAFW). This method uses BERT pre-trained review text to generate comment word vectors.
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