Exploring The Sequential Usage Patterns Of Mobile Internet Services Based On Markov Models

The rapid development of smart mobile devices and 4G networks,offers great business opportunities for mobile Internet service providers.Various mobile Internet applications benefit people's daily life and work,and people's access to Internet gradually shifts from personal computers to mobile devices.When people use the mobile Internet business,a large amount of individual behavior data is generated.The data describes the service type,time,place and other information,and contains the user's behavior and the preference for business.With the development of big data technology and the increasingly fierce competition in the mobile Internet,enterprises pay more attention to find out useful information from the user behavior data,and use the information to guide the business operation and strategy formulation.Through the analysis of user behavior data and the clustering of users,enterprises can provide targeted services and marketing activities for different types of users.In this research,we propose an innovative user classification method.We firstly construct a user's behavior model with user's behavior data,and use the model to describe the user's behavior rule,and calculate the difference between the user models to formulate distance matrix of the users.Then we use clustering method on the basis of distance matrix to classify users,extract the behavior preference and law of different types of users.Finally,based on the results of the analysis of the user's behavior,we provide a constructive suggestion for the enterprise's product design,operation and marketing strategy.It has a very important reference value for mobile Internet enterprise.