Design And Implementation Of Mobile Phone Application Recommendation System Based On Big Data Technology

In recent years,the number of mobile phone users has a rapid growth,mobile phone Android operating system updates constantly,mobile phone applications also show explosive growth trend,more and more mobile phone applications appear in a variety of application stores.As a mobile phone user,it is difficult to find out the mobile phone application that suits one's own interest from so many choices.For mobile phone application company,it is a major consideration to grasp the user interest,delineate the high quality of the potential user groups,promote their own mobile phone applications effectively,reduce marketing costs,and improve the mobile phone application installation rate to obtain greater economic benefits.When users use mobile phone applications,log information will be generated continuously.These log messages contain various kinds of information such as application type,time and place of use and so on.It is an important data source for mining user's interest.Users' interests can be analyzed through log information which the third party Android operating system company collects form the user mobile phone users and user tags.For a specific mobile phone application,recommend system can find high-quality potential user groups to improve installation rate.The paper implements a recommendation system for mobile applications based on big data technology.Since the log information generated by mobile phone users is large,in order to ensure the timely processing of data,big data technology is used to complete the data warehouse module,the user's different categories of information are stored in the different tables.The user tag module gives different labels to the user and the labels are stored in the non-relational database for the system to query statistics visually.Recommendation system module uses collaborative filtering algorithm to select potential user groups for specific mobile applications to improve the installation rate.In the process of practical application,this system provides a solution for the problem of low installation rate of mobile phone applications,and improves the installation rate effectively.According to the results of user profile,it can show user distribution by different topics and dimensions,and provide data support for the next strategic decision for the company.