Internet big data matching method

Abstract

The present invention discloses an Internet big data matching method. The method comprises the following steps: registration information of a user client is acquired; the user client automatically records information viewed by a user, and after classifying the information viewed by the user, uploads the information into a cloud server for encryption; and the cloud server performs priority allocation on the information according to an order in which the user views the information, and establishes a one-to-one mapping relationship between encrypted information of a same user and the registration information of the user. According to the method, the user information is recorded and classified automatically by the cloud server, so as to learn about the habits and demands of the user, and thus recommend appropriate advertisement information to the user; and a time mechanism is also introduced, and when the user has not viewed a class of information that the user viewed before at the user client for a set number of days, the cloud server determines that the user has lost interest in the class of information and will not recommend product information of the same or similar class, so that user experience is further improved.

Description

technical field [0001] The invention relates to a matching method, in particular to an Internet big data matching method. Background technique [0002] Obtaining users' behavior habits is the information that Internet information providers in the network environment most hope to obtain. By acquiring users' behavior habits, it is possible to make advertisement pushes more precise, make more accurate analysis of the audience of Internet products, and optimize charging strategies, etc. One solution in the prior art is to bind a user account with a terminal, and only allow the bound user terminal to log in to the account. The disadvantage of this method is that it is inconvenient for normal users. Especially when the user changes the terminal, such as a new mobile phone, it will bring very cumbersome operations, thereby affecting the user experience. In addition, some existing matching methods cannot accurately match customer needs. At the same time, after the user demand per...

AI Technical Summary

Problems solved by technology

The disadvantage of this method is that it is inconvenient for normal users

Especially when the user changes the terminal, such as a new mobile phone, it will bring very cumbersome operations, which will affect the user experience

In addition, some existing matching methods cannot accurately match customer needs. At the same time, after the user demand period, they cannot be adjusted in time, which has a great impact on user experience.