基于电影数据的个性化推荐技术应用研究

Research on the Application of Personalized Recommendation Technology Based on Movie Data

在数字化和和网络环境下,电影数据的个性化推荐能有效解决用户的不同需求。本文重点研究基于内容的推荐技术,基于用户的协同过滤推荐技术和基于物品的协同过滤推荐技术,从检索时间,准确度等方面来对比分析这三种推荐技术的不同,在一定程度上可以依据实际需求来选择不同的推荐技术,从而提高电影推荐的实用性。

In the digital and network environment,the personalized recommendation of movie data can effectively solve the different needs of users.Recommendation technology basement is mainly studied,based on the user’s collaborative filtering recommendation technology and the collaborative filtering recommendation technology based on items,the search time,accuracy to comparative analysis of the three aspects such as recommendation technology,to a certain extent,can be based on actual needs to choose different recommendation technology,so as to improve the practicability of movie recommendation.