Design And Implementation Of Mobile Consumer Behavior Analysis System Based On Big Data

As the fourth generation mobile communication network(IMT-Advanced)technology is widely used in China,China's mobile operators,one of the three largest telecommunications operators in China,are the first companies to apply the popular 4G communication technology.Therefore,the analysis of mobile users' consumption behavior and the extraction of indicators are gradually promoted.And data mining analysis and processing efficiency requirements.Those lower-level information management methods have been far from meeting the current mobile companies to obtain a large number of data needs,so the design and implementation of an advanced technology,can effectively obtain data and timely analysis and processing of consumer behavior analysis system in line with the trend of the times,is the current mobile company consumer behavior index.Very important research contents of target analysis,mining and extraction.In order to enable mobile operators to efficiently analyze the consumer behavior of mobile users and the communication needs of mobile users,a user consumption behavior analysis system is designed and implemented by mining and analyzing a large number of user data and extracting effective indicators.The main contents of the research are as follows:1?In this paper,the use of 4G communication technology in China is analyzed to show the necessity of building consumer behavior analysis system.Then,the research status of consumer behavior analysis system at home and abroad is described in detail.At the same time,the current popular and new data mining technology and index analysis and acquisition technology are analyzed and introduced in detail in the application process of the system,and the current mobile communication company consumer behavior data acquisition is obtained.Inconvenience,data analysis and data processing efficiency is very low.2?Based on the problems mentioned above,such as the difficulty and inefficiency of user consumption data analysis and processing,this paper mainly uses Bayesian algorithm based on data mining technology to classify user data,and uses incremental learning to complete user consumption behavior analysis.The classification and management of all kinds of data in the process.In addition,the system uses an incremental learning method based on Bayesian algorithm to optimize a large number of data for user consumption behavior analysis model,so as to achieve an effective location of mobile users' consumption interval,mobile users' consumption behavior indicators for effective analysis and processing of data and access to those consumer intentions are not.Obvious mobile users,to give them reasonable consumption behavior positioning,etc.The innovation of this subject mainly includes the following contents:1?After a long-term analysis of the consumer behavior index data of mobile users,these index data are classified in detail by an incremental learning method based on Bayesian algorithm,which can uninterruptedly optimize the analysis model of consumer behavior,and finally complete the analysis of consumer data of mobile users.Fruit feedback improves the data processing ability of the whole system.2?The application process of data mining technology used in user behavior analysis system is analyzed and introduced.The general method and basic operation flow of data mining technology used in this system are also introduced.3?The user's consumption index extracted and analyzed by the system is displayed by the representation method of JFree Chart chart.At the same time,the user's consumption index data stored in the multi-dimensional relational management database is acquired and the user's consumption index data stored in the process of extracting the user's consumption index data by the technology of behavior index calculation.Calculation.In the research and design process of user behavior analysis system,RUP development workflow and object-oriented analysis management principles have been followed,providing mobile companies with a new efficient user behavior data acquisition tool.Through the actual application results show that in the process of analyzing and extracting consumer behavior indicators,the use of data mining technology can effectively solve the problems of data statistical analysis and inconvenience in acquisition,thus enhancing the competitiveness of mobile companies in the current 4G communication market,but also to the current major operators in the user's consumer behavior.Consumption index analysis provides a good example.