A Recommendation Approach Based on Product Attribute Reviews: Improved Collaborative Filtering Considering the Sentiment Polarity

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A Novel Deep Hybrid Recommender System Based on Auto-encoder with Neural Collaborative Filtering

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Leveraging unified deep neural networks to augment product recommendations

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Deep learning sentiment analysis recommender system framework for an intelligent product recommendations

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AELA-DLSTMs: Attention-Enabled and Location-Aware Double LSTMs for aspect-level sentiment classification

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Integrating Collaborative Filtering and Matching-based Search for Product Recommendations

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Feature Frequency Inverse User Frequency for Dependant Attribute to Enhance Recommendations

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Employing user attribute and item attribute to enhance the collaborative filtering recommendation.

An Intelligent Deep Neural Sentiment Classification Network

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