个性化电影推荐算法综述

Review of Personalized Movie Recommendation Algorithms

大数据时代,各类影视资源纷纷涌现,“信息过载”问题在影视行业愈发凸显,有效的电影推荐算法是解决这个问题的关键。本文首先总结了电影推荐的主流推荐算法,主要有协同过滤、基于内容的推荐和混合推荐三类算法,然后比较分析了几种推荐算法的优缺点。最后,针对推荐算法的发展方向,又对基于上下文的推荐算法进行了简单的介绍。

In the era of big data,all kinds of film and television resources have emerged,and the problem of"information overload"has become increasingly prominent in the film and television industry.Effective film recommendation algorithm is the key to solve this problem.This paper first summarizes the mainstream recommendation algorithms of film recommendation,including collaborative filtering,content-based recommendation and hybrid recommendation,and then compares and analyzes the advantages and disadvantages of several recommendation algorithms.Finally,according to the development direction of recommendation algorithm,the context based recommendation algorithm is briefly introduced.