Information recommendation method and system based on big data

Abstract

The embodiment of the invention relates to the technical field of information recommendation, and particularly discloses an information recommendation method and system based on big data. According to the embodiment of the invention, activity analysis is carried out; performing browsing information statistics and screening on the active browsing data; performing label identification on the inactive browsing data; and recommending the multiple pieces of interest recommendation information to an inactive user corresponding to the inactive browsing data. Activeness analysis can be carried out according to information browsing data of multiple users, browsing information statistics and screening are carried out on the active browsing data of active users, label identification is carried out, a label information arrangement database is obtained, and then the interest labels of non-active users are used for identifying the interest labels of the non-active users. And the interest recommendation information is matched from the label information arrangement database for recommendation, so that corresponding information with high page views of the active users can be recommended according to the interests of the inactive users, the information recommended to the inactive users can meet the interests of the users as much as possible, and the situation that the activeness of the inactive users is lower and lower is avoided.

Description

technical field [0001] The invention belongs to the technical field of information recommendation, and in particular relates to a method and system for information recommendation based on big data. Background technique [0002] With the development of big data technology and various software technologies, information recommendation has become particularly important, especially in news information software. Only by recommending more content that meets users' interests can users increase their online time and ensure more activity. users, thereby promoting the development of the software. [0003] The existing information recommendation methods usually recommend related information according to the type of interest selected by the user. Although this information recommendation method can recommend some interesting content to the user to a certain extent, most of the information is not available. It cannot really arouse the user's interest, especially for some users who are not...

AI Technical Summary

Problems solved by technology

[0003] Existing information recommendation methods usually recommend relevant information based on the type of interest selected by the user. Although this information recommendation method can recommend some interesting content to the user to a certain extent, most of the information does not Can't really arouse users' interest, especially for some users who are not very active. If more than half of the recommended information cannot arouse users' interest, it may cause users to become less and less active

Images