基于Spark大数据处理的电影推荐系统设计与实现

Design and implementation of film recommendation system based on spark Big Data processing

文章指出,该系统的开发设计是使用了互联网著名且优化过后的MovieLens数据集当作基础,以网络中某个电影评分网站的数据业务框架作为前提,其中包括离线推荐和实时推荐体系,总体采用了协同过滤算法和基于内容的推荐算法实现混合推荐的目的。实现了前端可视化页面、后台业务处理、算法的设计与实现、环境的安装与部署等多种操作方式。

The development and design of the system uses the famous and optimized MovieLens data set of the Internet as the basic dependence,and takes the data business framework of a movie scoring website in the network as the premise.It includes offline recommendation and real-time recommendation system.Collaborative filtering algorithm and content-based recommendation algorithm are used to realize mixed recommendation.The realization of front-end visualization page,background business processing,algorithm design and implementation,environment installation and deployment and other multi-operation implementation.