Information recommendation method and device, equipment and storage medium

Abstract

The invention relates to the technical field of information recommendation, in particular to an information recommendation method and device, equipment and a storage medium, and the method comprises the following steps: in response to an information recommendation request, determining respective corresponding recall information sets from a preset information base by utilizing a plurality of different recall strategies; obtaining historical data of information recommendation, and determining a correction parameter of each recall strategy based on the historical data; determining an actual recall gear corresponding to each recall strategy according to the correction parameter of each recall strategy and a preset recall gear; for each recall strategy, determining a candidate recommendation information set from the recall information sets corresponding to the recall strategies based on a preset sorting model and the actual recall gear; and determining a preset amount of information from the candidate recommendation information set corresponding to each recall strategy, and recommending the information to a target user. According to the information recommendation method, the information recommendation effect can be ensured, and the diversity of the recommended information can be improved.

Description

technical field [0001] The present invention relates to the technical field of information recommendation, in particular to an information recommendation method, device, equipment and storage medium. Background technique [0002] With the advent of the era of big data, the recommendation system has become the best solution for the public when faced with the problem of screening massive Internet information. The core of a recommender system is a recommender engine, which aims to provide users with the desired information by filtering useful information from a large amount of data. The recommendation engine can mine sample patterns in the data set by storing and analyzing historical information such as user behavior logs and item ratings, further analyze user characteristics, and generate recommendation information that is jointly related to user needs and interests. These recommendation systems not only bring convenient information screening services to users, but also enric...

AI Technical Summary

Problems solved by technology

This method treats all recall algorithms equally and ensures the diversity of recommended information, but it cannot reflect the pros and cons of each recall strategy, which affects the effect of information recommendation

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