User behavior analysis method based on charging information

Abstract

The invention discloses a user behavior analysis method based on charging information. A system comprises a charging data module, a business logic module, a geographic information system module, a data analysis module and the like. According to the system, original data of a call bill of a user is acquired, charging data is analyzed, user behavior data in the charging data is extracted, a user behavior model is established via user dimension and behavior dimension, a multi-dimensional dataset is established via dimension models, and user behaviors are subjected to macroscopic and microscopic behavior analysis. Original user behavior bill data is analyzed, the dimensional models are used, and accordingly a user behavior statistical and analytical service for user communication behaviors is provided.

Description

technical field [0001] The invention relates to technical fields such as software and mobile communication, in particular to a user behavior analysis method based on billing information. Background technique [0002] With the development of mobile communication technology and software technology, especially the development of billing-based technology and intelligent data analysis technology, it provides feasibility for a user behavior analysis method based on billing information. [0003] At present, voice users, especially mobile voice users, have been greatly popularized, and the traffic volume of users is increasing. Following this, the communication network generates a large amount of billing data for user behavior, which records the user's Communication behavior, the current main way of use is to extract billing information generated by users using services to generate bills, which is only used for simple billing, and does not dig out valuable information from a large a...

AI Technical Summary

Problems solved by technology

[0005] In many current business promotions and information pushes, in many cases, there is no targeted matching based on the user's attributes and behavioral characteristics, which is inefficient. It is mainly covered by the amount of data. feature data, which becomes a way to improve efficiency

[0006] In the face of big data, the traditional mode of processing massive information has various disadvantages, such as development difficulties, low calculation efficiency, and the inability to view data slices from different angles in real time from multiple dimensions. The emergence and development of business intelligence, in order to solve these The problem provides feasibility. Business intelligence can quickly discover and extract effective user characteristic behavior data in massive data, and can find out the correlation of user behavior characteristics through various intelligent algorithms and make predictions. Through business intelligence technology, massive user behavior Multi-dimensional modeling and analysis of data, extracting user behavior characteristic data contained in massive data, can greatly improve the grasp of user behavior characteristics

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