Method and system of automatically generating report form on basis of different information sources

Abstract

The invention relates to a method and a system of automatically generating a report form on the basis of different information sources. The method includes: step 1, acquiring static information data of a user from a first information source; step 2, acquiring dynamic information data of the user from the second information source; step 3, analyzing the acquired static and dynamic information data,carrying out data cleaning, and obtaining data, which are required for generating the report form, after filtering/formatting, wherein the data required for generating the report form include multiple tags of the user; step 4, calculating weights for all the tags of the user according to the data and the tags obtained in the step 3; and step 5, combining calculation results of the step 4 with thedata of the step 3 to form a data set containing all dimensions of the user. According to the method, the different sources of the data are taken into account, differentiated processing is carried out, and fineness and accuracy of processing are improved; timeliness of the user data is taken into account, and a data updating mechanism is established; and a user profile is used as reference information, transaction speeds of related services are greatly increased, and customer relationship management is enabled to be more precise.

Description

technical field [0001] The invention relates to the technical field of Internet services, in particular to a method for automatically generating reports based on different information sources. Background technique [0002] With the explosive development of the Internet, a large amount of data is generated every day. How to effectively analyze the massive data and find favorable specifications or information from it has become a trend. [0003] In the traditional method, it is necessary to manually classify and judge user behavior, and provide targeted services or other processing responses in the later stage. In the scenario of massive data, the data often has many dimensions and a large amount of data, and it is difficult to collect comprehensive statistics of indicators related to user behavior manually. In addition, due to people's fatigue and other situations, the accuracy rate of this traditional manual recognition method is not high. [0004] After the Internet gradu...

AI Technical Summary

Problems solved by technology

[0005] However, at present, the identification of user tags and the establishment of user portraits are mainly completed through manual intervention and simple computer processing conversion, which has the following shortcomings: 1. It takes a long time; 2. High labor costs; 3. Generate The result is not intuitive enough; 4. Information entry has the risk of error caused by manual work

[0006] In ad

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