Abstract
In the Internet era with rapid data growth, it is difficult for users to quickly find the project information they need from the massive information on the Internet. As a technology based on data mining, the recommendation system effectively solves the problem of information overload. Collaborative filtering recommendation is a classic and effective recommendation algorithm. It focuses on the relationship between the user’s interest preferences and items. The purpose is to recommend items that meet the user’s interest preferences, such as product recommendation, audio recommendation, tourist attraction recommendation, etc. The field has a wide range of applications. Therefore, this article introduces the principle and related properties of collaborative filtering, as well as its improvement and application, and discusses future trends and directions for improvement.
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Pan, L., Shao, J. (2021). Review of Improved Collaborative Filtering Recommendation Algorithms. In: Yu, Z., Patnaik, S., Wang, J., Dey, N. (eds) Advancements in Mechatronics and Intelligent Robotics. Advances in Intelligent Systems and Computing, vol 1220. Springer, Singapore. https://doi.org/10.1007/978-981-16-1843-7_3
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DOI: https://doi.org/10.1007/978-981-16-1843-7_3
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