Method for cross-over analysis of user behavior

Abstract

The invention discloses a method for cross-over analysis of a user behavior. The method comprises the following steps: establishing a user database, wherein a plurality of dimensionalities are arranged in the user database and one or more label names are arranged on each dimensionality; collecting and storing use data of multiple users in a user data set in the user database, wherein the user data of each user comprises a user ID and a matched label name of the user on one or more dimensionality; collecting and storing the label data corresponding to each dimensionality in a label set of the use database, wherein each label data comprises a label name and a plurality of user visiting cards matched with the label; presetting a cross-over analysis calculation strategy, calling for the user data set and / or the label set according to the cross-over analysis calculation strategy, and extracting the user data and / or the label data in the user data set and / or the label set; utilizing the cross-over analysis of calculation strategy to perform analysis calculation on the extracted user data and / or label data, thereby acquiring the user behavior data.

Description

technical field [0001] This application relates to the fields of data integration and data optimization, in particular, a method for cross-analyzing user behavior. Background technique [0002] In the context of the current highly active Internet field, especially in popular sectors such as online video, e-commerce, social platforms or instant messaging, there is fierce competition. Internet companies are Internet service providers; on the one hand, they are constantly optimizing, improving and transforming the original business to stabilize the existing user groups; on the other hand, they are committed to developing more novel and dynamic new Business, to keep up with the dynamics of the industry, to obtain more new users and attention. In the final analysis, being able to provide a better user experience than competitors is the key to attracting users. [0003] On this basis, if we want to continuously improve the user experience, it will be very important to fully und...

AI Technical Summary

Problems solved by technology

It can be seen that the defect of the existing technology is that the collection range of user behavior data is not wide enough, and the number of samples is small, so the space for analysis is very limited; especially in today's big data environment, the resource of "user behavior" has not been realized. Take advantage of

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