引用文献介绍基于内容的推荐算法

基于内容的推荐算法是一种将用户的历史行为和偏好与物品的属性进行匹配，从而推荐相似物品给用户的推荐算法。该算法的核心思想是通过对物品的属性进行分析和建模，找到与用户历史偏好相似的物品，从而实现个性化推荐。

以下是一些引用文献，介绍基于内容的推荐算法：

1. Lops, P., de Gemmis, M., & Semeraro, G. (2011). Content-based recommender systems: State of the art and trends. In Recommender systems handbook (pp. 73-105). Springer US.

2. Pazzani, M. J., & Billsus, D. (2007). Content-based recommendation systems. In The adaptive web (pp. 325-341). Springer Berlin Heidelberg.

3. Adomavicius, G., & Tuzhilin, A. (2005). Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering, 17(6), 734-749.

4. Chen, L., Wang, X., & Zhang, Y. (2019). A content-based recommendation algorithm based on item similarity and user preference. Journal of Ambient Intelligence and Humanized Computing, 10(5), 1841-1852.

5. Hu, Y., Koren, Y., & Volinsky, C. (2008). Collaborative filtering for implicit feedback datasets. In Proceedings of the 2008 Eighth IEEE International Conference on Data Mining (pp. 263-272). IEEE.