Information recommending method, information recommending device and mobile terminal

Abstract

The invention discloses an information recommending method, an information recommending device and a mobile terminal. The information recommending method comprises the following steps of providing an information display page in which a plurality of classifying labels are displayed; respectively acquiring user preference marks of a plurality of information contents corresponding to each classifying label; acquiring user preference information corresponding to each classifying label according to the corresponding user preference mark; and managing the labels of the information displaying page according to the user preference information of the classifying labels; and performing information recommendation according to the classifying labels displayed in the information displaying page after the labels are managed. By the information recommending method of an embodiment, information contents which attract a user can be accurately determined, so that personalized information can be accurately recommended for the user. Moreover, the user does not need to set marks when the user preference information corresponding to the classifying labels is acquired, and the user experience is smooth and natural.

Description

technical field [0001] The present invention relates to the technical field of the Internet, in particular to an information recommendation method, device and mobile terminal. Background technique [0002] With the rapid development of Internet technology, personalized recommendation has become one of the indispensable network services in people's network life, and has also become a focus of the future development of Internet products. [0003] At present, the existing personalized recommendation schemes mainly include: 1. The user sets favorite or interested categories according to his own interests, and the system obtains corresponding recommendation information according to the preferences or interested categories set by the user, and recommends them to the user. For example, taking news recommendation as an example, if the user sets the news categories of interest as current events, sports, etc., the system can obtain corresponding hot news content and sports news conten...

AI Technical Summary

Problems solved by technology

[0004] However, the problem with the above scheme is that whether the user sets preferences or categories of interest, or enters his attitude towards the page through the buttons on the browsed page, it all depends on the user's own operation, which increases the user's operation. cost, and because some users have limited time and energy to choose tags by themselves, or because they are unwilling to set preferences or categories of interest in view of personal privacy, at this time, recommendations can only be made for specific users based on the preferences of most users, resulting in The accuracy of the recommendation results is reduced, and the user experience is poor

Images