Research And Implementation Of APP User Activity Enhancement Based On HADOOP

With the popularization of Internet in daily life more and more widely,the Internet has become an indispensable part of people's lives,in the background of the APP software,to a certain extent,solve a lot of problems in people's lives,APP consumption has become an important part of information consumption in the network.Although the development prospect of APP software is wide,there are still many problems in the current APP software recommendation.The current situation of users of Hadoop based on APP software,using APP software to identify the impact of users using active factors,are related to the APP recommended in the user APP consumption according to the user's preference,so as to effectively improve the user activity in the platform,and then be able to use this system to enhance the user experience on the platform effectively the promotion of APP platform's overall activity has very important significance.Through Hadoop technology,we analyze the browsing records,click rates and evaluation scores of users in APP,make statistics and analysis,and find out what users are interested in,which are the contents of user's antipathy,then adjust and optimize APP functions.Recommend accurate content to users,for example,according to user's click and browse behavior,use collaborative filtering algorithm to recommend interested columns or contents to users,and implement them with Hadoop,in order to improve user activity.