Resource characteristic and user preference-based resource matching recommendation method and system

Abstract

The invention discloses a resource characteristic and user preference-based resource matching recommendation method and system. The system comprises resource information, a user system and a user, wherein the user system comprises an extraction system module, a decision-making system module and a push system module; the extraction system module comprises a user behavior characteristic extraction module, a user preference extraction module and a resource information characteristic extraction module; the extraction system module extracts the information and then transmits the information to the decision-making system module; and the decision-making system module analyzes the information and then pushes the information to the user through the push system module. According to the resource characteristic and user preference-based resource matching recommendation method and system, the disadvantages in the prior art are overcome; the design structure is reasonable; association can be carried out on the basis of the characteristics of different dimensions of the resource and the historical preference of the user according to a resource characteristic and user preference-associated data analysis method; the algorithm and the precision are well considered; and dynamic push can be carried out according to the historical behavior characteristics of the user on the basis of a method for analyzing historical behaviors of the user.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a resource matching recommendation method and system based on resource characteristics and user preferences in a network system. Background technique [0002] With the development of Internet technology, more and more resources (including information, content, services, etc.) The distance between people and people, between people and services has been shortened. However, the rapid development of the Internet and mobile Internet, in addition to bringing convenience to our work and life, there are also confusing problems brought about by the explosive growth of various resources. How to find suitable resources among the massive information, content, and services , is a topic worth studying. [0003] In addition to active acquisition, there are generally three ways to obtain various resources at present: (1) The server pushes the content to the user indiscriminately. Th...

AI Technical Summary

Problems solved by technology

The algorithm of this method is relatively simple, but because it does not consider the differences between users, the accuracy will be slightly lower

[0004] The existing resource push methods are either undifferentiated recommendation with poor push accuracy, or manual recommendation, which is time-consuming and laborious, or extraction of user preferences, the algorithm is complex and inefficient, or extraction of correlation features between resources is slightly less accurate

In terms of the number of resource pushes, the needs of users are not fully considered. Too many pushes or too few pushes will either form spam or fail to meet the user's demand for resources.

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