基于个性化推荐系统的视频App的设计  

The Design of Video App Based on Personalized Recommendation System

作　　者：马学明 童怀[1] MA Xue-ming;TONG Huai(School of Information Engineering,Guangdong University of Technology,Guangzhou 510000,China)

机构地区：[1]广东工业大学信息工程学院,广东广州510000

出　　处：《电脑知识与技术》2021年第8期4-6,共3页Computer Knowledge and Technology

摘　　要：近年来,各类视频应用上内容越来越丰富,页面上与当前用户无关的内容也越来越多。因此,市面上出现了多种不同的推荐算法来进行内容推荐。但是,不是每种推荐算法都能够解决所有的问题。基于个性化推荐系统的视频App,融合了多种推荐方法。首先为了解决推荐系统的冷启动问题,采用了基于统计学的推荐方式,同时,采用基于协同过滤的推荐算法,计算视频和用户间的隐藏特征,最后还有实时推荐模块,能够根据用户近期的行为对推荐内容进行调整。In recent years,the content of various video applications is becoming more and more abundant,and there are more and more content on the page that has nothing to do with the current users.Therefore,there are many different recommendation algo⁃rithms in the market for content recommendation.However,only use a recommendation algorithm can not solve all the problems.The video App based on personalized recommendation system integrates various recommendation methods.Firstly,in order to solve the cold start problem of the recommendation system,a recommendation method based on statistics is adopted.At the same time,a recommendation algorithm based on collaborative filtering is adopted to calculate the hidden features between video and users.Fi⁃nally,there is a real-time recommendation module,which can adjust the recommended content according to the recent behavior of users.

关 键 词：ANDROID应用 推荐系统 协同过滤 ALS算法 实时推荐 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]