Research On Personalized Recommendation Mechanism Of News APP Aggregation

In the Internet society,big data is widely used in all aspects of people's lives,which increases the convenience for people to obtain information,but it also implies a crisis.In today's society,mobile phones have become the main tool for people to obtain information anytime,anywhere.However,there are more channels for obtaining information,and various types of news apps are emerging.It is difficult for audiences to see the information they need.In addition,people have a fast pace of life and lack the entire reading time.There is an urgent need for a fast and efficient way to read news.The aggregated news app aggregates multiple types of news information on one platform,eliminating the inconvenience of multi-channel reading.At the same time,the aggregated news app uses a personalized algorithm recommendation mechanism to tailor news content for users,meet users' fragmented reading needs,and make reading more efficient."Toutiao" is a typical representative of domestic aggregated news apps,and one of the earliest news apps to explore personalized recommendation technology.This article selects "Toutiao" as a case.From the perspective of journalism and communication,this paper studies the problems in the selection and recommendation of news information on the aggregation news platform,and proposes corresponding solutions.The introduction section mainly analyzes the current status of research on this topic at home and abroad,and explains the research methods and innovations and difficulties of the research.The second part mainly summarizes relevant news app and personalized recommendation mechanism.The third part mainly analyzes the application mode,content management,value orientation and other aspects of the personalized recommendation of "Toutiao".From this,we can know the current status of various aggregate news platforms.The fourth part mainly looks at the common problems of the aggregate news app from the "Toutiao".The fifth part mainly proposes solutions based on the problems analyzed in the fourth part.The personalized recommendation mechanism adapts to the needs of the development of the times,is widely used in various fields,and is gradually becoming popular.It has a strong influence,and it is no exception for news information platforms.In order to avoid weaknesses,better use personalized recommendation technology to serve the audience,purify the information ecological environment,and promote a virtuous circle of the media environment,the author believes that it is necessary to analyze and research possible problems to maintain the authenticity of the news and not blindly raise it.The status of machine algorithms.