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PlatypusCollaborator
- Linux系统下的SVD方法。应用协同过滤方法实现SVD特征的提取。完成推荐系统的描述。-SVD method Linux system. Collaborative filtering method applied to achieve SVD feature extraction. Complete descr iption of the recommended system.
recommender-
- Collaborative Filtering，基于Collaborative Filtering，建立主动为用户推荐商品的推荐系统。实现参考协同过滤算法或它的优化，实现并改进算法，计算出每个客户对未购买的商品的兴趣度，并向客户主动推荐他最感兴趣的N个商品。实验数据可以从MovieLens.com下载。要求使用至少10，000不同用户的数据，至少1000个不同的movie。-Collaborative Filtering，Based C
CollaborativeFiltering
- 推荐系统中的经典算法，协同过滤算法，基于用户和基于项目的-Recommended system classical algorithm, collaborative filtering algorithm based on user and project-based
CF_Movie
- 电影推荐系统 协同过滤推荐 Java源码-MovieLens Colleboration Filtering Recommendation System
MyMapReduce
- 使用MapReduce实现的给予项目的协同过滤算法，只实现了构建用户向量和协同矩阵，仅供参考-Give the project implemented using MapReduce collaborative filtering algorithm, only to realize the construction of the user vector and collaboration matrix, for reference
user-based
- 使用的数据集是BX-CSV-Dump，基于用户的协同过滤，有详细代码注释-英语 Data sets used are BX-CSV-Dump, user-based collaborative filtering, a detailed code comments
Collaborative-Filtering
- u1.base和u1.test为训练集和测试集，分别来自MovieLens数据集， 本程序只是很简单的基于用户的协同过滤算法 运行算法所需要的配置信息，包括读取训练集和测试集还有最近邻个数的选择都在Base.java文件中可以找到 本程序的主程序是Application.java 仅供参考，希望对大家有帮助-Collaborative Filtering
javascript
- 用javascr ipt脚本实现基于用户的协同过滤算法-Javascr ipt scr ipts with user-based collaborative filtering algorithm
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
UserCF
- 推荐算法，基于用户的协同过滤算法，python 实现，简单快速。-recommend algorithm ,collaborate filter algorithm based on user ,python implement.simply and fast
doubanWebSpider
- 快速搭建Spring + SpringMVC + Mybatis平台 使用ALS协同过滤推荐模型构建图书推荐模型 使用Python搭建推荐服务，与Java服务用Json进行数据交互 NLTP情感分析 -using Spring+ SpringMVC+ Mybatis recommend system
cf_matrix-decomposition
- 现在比较常用的一种给予举证分解的协同过滤算法，用于个性化推荐-Now more commonly used as a collaborative filtering algorithm decomposition give evidence for personalized recommendation
cf
- 现在比较常用的一种传统的协同过滤算法，用于个性化推荐 最基础的-Now more commonly used as a traditional collaborative filtering algorithms for the most basic personalized recommendation
usercf
- 基于用户的协同过滤算法(Python实现) ,很好的学习协同过滤算法的资料-User Based Collaborative Filtering
spark
- MLlib 是spark 机器学习的库，它的目标是使机器学习算法能更容易上手。这个库包含通用学习算法和工具集，包括：分类，回归，聚类，协同过滤，降维，以及深层优化策略和上层管道API（pipeline）.-MLlib is spark machine learning library, which aims to make a machine learning algorithm can be more easy to use. Thi
CollaborativeFiltering-master
- MATLAB实现协同过滤。可以实现协同过滤算法，对诸如电影、书籍等进行推荐-cross-filter with matlab-MATLAB realization of collaborative filtering. Can achieve collaborative filtering algorithm, such as movies, books, etc. Recommended-cross-filter with matla
Recommender
- 基于MovieLens数据，通过计算余弦相似度，Python语言构建的一个简单协同过滤推荐系统，并给出RMSE等测评结果-Based MovieLens data by calculating the cosine similarity, Python language to build a simple collaborative filtering systems, and the like are given RMSE uati
cofe
- 基于协同过滤推荐recommendation的电影推荐系统源码-Movie recommendation based on collaborative filtering recommender system source code
CollaborativeFiltering
- 基于模糊聚类的协同过滤算法，是一篇讲算法的文章，没有具体实现，为caj文件，需用特定阅读器打开-Fuzzy clustering algorithm based on collaborative filtering, the article is an article about the algorithm, there is no specific implementation for caj documents required s
CF
- Python实现协同过滤算法，即Collaborative Filtering(CF)，数据集为MovieLens电影推荐和书籍推荐数据集-Python implementation of collaborative filtering algorithm, namely Collaborative Filtering (CF), the data set is recommended MovieLens movie and book