协同过滤推荐算法是诞生最早，并且较为著名的推荐算法。主要的功能是预测和推荐。算法通过对用户历史行为数据的挖掘发现用户的偏好，基于不同的偏好对用户进行群组划分并推荐品味相似的商品。协同过滤推荐算法分为两类，分别是基于用户的协同过滤算法(user-based collaboratIve filtering)，和基于物品的协同过滤算法(item-based collaborative filtering)，本算法是基于用户的协同过滤算法(user-based collaboratIve filtering)。(Collaborative filtering recommendation algorithm is the earliest and well-known recommendation algorithm. The main function is prediction and recommendation. The algorithm discovers users'preferences by mining users' historical behavior data, divides users into groups based on different preferences and recommends products with similar tastes. Collaborative filtering recommendation algorithms are divided into two categories: user-based collaborative filtering and item-based collaborative filtering. This algorithm is based on user-based collaborative filtering.)