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Applying Deep Learning Models to Analyze Users' Aspects, Sentiment, and Semantic Features for Product Recommendation
2022
Applied Sciences
As there is a huge amount of information on the Internet, people have difficulty in sorting through it to find the required information; thus, the information overload problem becomes a significant issue for users and online businesses. To resolve this problem, many researchers and applications have proposed recommender systems, which apply user-based collaborative filtering, meaning it only considers the users' rating history to analyze their preferences. However, users' text data may contain
doi:10.3390/app12042118
fatcat:qvu6jzwx5beo7hgpn5o7gxtyzm