搜索资源列表
ItemCF
- 推荐算法，基于物品的协同过滤算法，python实现，简单快速-recommend algorithm ,base on item collaborate filter .python implement .simple and fast
itemcf
- Hadoop平台上的物品协同过滤程序，使用Java语言编写(A Item Collaborate Filter Program based on Hadoop platform written by Java)
ItemCF
- 基于商品的协同过滤算法,主要用于推荐系统中(The project has been used in our recommended system, and hope to help you)
MovieLens-RecSys-python2
- 基于Movielens 1M数据集分别实现了User Based Collaborative Filtering（以下简称UserCF）和Item Based Collaborative Filtering（以下简称ItemCF）两个算法.(Implementation of collaborative filtering based on UCF/ICF)
CF
- Java编写基于用户和基于项目的协同过滤的代码实现，数据集为movie_lens100k(ItemCF, UserCF based on Java)
movie_recommend-master
- 基于Spark ALS实现协同过滤，基于内容的过滤、基于用户的协同过滤(Spark ALS Collaborative filtering, Content based filterin,User based collaborative filtering)
recommend-system-master
- 协同过滤算法实现推荐过程，其中产生了协同过滤推荐矩阵，通过矩阵计算推荐数据(generate recommend result through ITEMCF)