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An Improved Dynamic Collaborative Filtering Algorithm Based on LDA
2021
IEEE Access
Currently, existing collaborative filtering (CF) algorithms usually use user behavior data to generate recommendations. The calculation of similarity between users is mainly based on ratings, without considering the explicit attributes of users. This paper proposes an improved dynamic collaborative filtering algorithm named hybrid dynamic collaborative filtering (HDCF), which is based on the topic model. Considering that the user's evaluation of an item will change over time, we add a
doi:10.1109/access.2021.3094519
fatcat:6m3iuvqtbjg6bkfbg34inmlmve