Design And Implementation Of Personalized Video Recommendation System

With the rapid development of science and technology,the Internet has facilitated people's lives,and people can watch video content on the network at any time.At the same time,a large amount of information covers people's lives,users can not quickly and accurately obtain the video resources they need,which invisibly reduces the user's product experience.Therefore,in order to solve the problem of information redundancy and improve the utilization of video information,the system(Xiaomi Video)provides personalized video recommendation function.In order to improve the accuracy of recommendation,this paper first adopts the collaborative filtering algorithm,and then applies the content filtering algorithm to filter the video content with different user interest in the recommended list,and provide users with personalized recommendation services for thousands of people.Based on the general recommendation system,this paper combines two commonly used recommendation algorithms to provide more accurate recommendation services.First of all,this paper describes in detail the background of this project and the necessity of personalized video recommendation service;introduces the development and research status of personalized recommendation system at home and abroad,and lays a foundation for later research and design.Secondly,the functional and non-functional requirements analysis of the personalized recommendation system is elaborated.The system is divided into video editing,personal homepage,video recommendation,video commentary,video collection,video search,membership system and other modules.The internal links of modules are compact and the coupling between modules is low.The analysis of the system architecture,process,data tables and interfaces of each module was designed.On this basis,each module was designed in detail.In the video recommendation module,the popular recommendation algorithms are analyzed and compared,and used a hybrid recommendation algorithm based on the collaborative filtering algorithm and the content filtering algorithm.By establishing the user's personal preference model,the user similarity calculation was performed to obtain the video content of interest to the user.Show it to the user.In addition,the author also participated in the development of video editing modules,personal homepage modules,video reviews,and video collection modules.In the video editing module,filter addition,music editing and other related functions are realized,and video can be uploaded to the network to provide users with more possibilities to express themselves.Finally,I have carried out functional testing and performance testing of the system to ensure the correctness and reliability of the system.The system designed in this paper comes from the actual project of Xiaomi Technology Co.,Ltd.,which has been developed and successfully launched.The project worked well,solved the pain points of users and reached the initial goal of the project.