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24 May 2022 Research on collaborative filtering recommendation algorithm based on temporal context
Jun Li, Ge Yu
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Proceedings Volume 12260, International Conference on Computer Application and Information Security (ICCAIS 2021); 122600N (2022) https://doi.org/10.1117/12.2637779
Event: International Conference on Computer Application and Information Security (ICCAIS 2021), 2021, Wuhan, China
Abstract
Collaborative filtering-based algorithms are widely used to make recommendations without analyzing the contents. Time effect can be seen everywhere in our daily life. User interests will change over time, so we use the time-decay function to integrate the user-item rating matrix and adjust it by different time-decay factors to optimize the model. And we conducted experiments using the improved algorithm on the movie evaluation dataset movielens-1 m. The results show that the algorithm is able to improve the accuracy and coverage of recommendations under specific time factors, and also can partly improve the recommendation efficiency.
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Jun Li and Ge Yu "Research on collaborative filtering recommendation algorithm based on temporal context", Proc. SPIE 12260, International Conference on Computer Application and Information Security (ICCAIS 2021), 122600N (24 May 2022); https://doi.org/10.1117/12.2637779
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KEYWORDS
Detection and tracking algorithms
Electronic filtering
Lithium
Information science
Information technology
Integration
Internet
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