基于协同过滤算法的电影个性化推荐系统设计与实现  

Implementation of Personalized Movie Recommendation System Based on Collaborative Filtering Algorithm

作　　者：贾忠涛[1] 

机构地区：[1]西南科技大学计算机科学与技术学院,四川绵阳621010

出　　处：《软件导刊》2015年第1期86-88,共3页Software Guide

摘　　要：随着互联网与移动终端的普及,网络上的电影娱乐信息数量海量增加,用户对电影个性化服务的需求日益旺盛。设计电影个性化推荐系统,该系统基于B/S模式,采用JavaEE体系架构。个性化电影推荐服务能够挖掘用户信息、电影项目信息间隐藏的关联性,从而发现用户的潜在兴趣,将用户可能感兴趣的影视片推荐给用户。With the rapid spread of the Internet and mobile terminals,movie entertainment information on the network increases in a large amount.For increasing demand for personalized movie service,apersonalized movie recommendation system was designed and implemented which is based on B/S model and architecture by JavaEE.Personalized movie recommendation services can find the hidden relevance among the users＇ information and movies＇ information,so as to find the potential interest of the user.Finally,the system recommends movies to user depending on user＇s interest.

关 键 词：个性化推荐 电影推荐 协同过滤 JavaEE架构 

分 类 号：TP319[自动化与计算机技术—计算机软件与理论]