Image recommendation method and device, electronic equipment and storage medium

By fusing image features and behavioral features and dynamically adjusting the random number generator, the problem of inaccurate recommendation results in existing image recommendation methods is solved, thereby improving user experience and device usage frequency.

CN122153101APending Publication Date: 2026-06-05SHENZHEN LUKA DR TECHNOLOGY CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
SHENZHEN LUKA DR TECHNOLOGY CO LTD
Filing Date
2024-12-03
Publication Date
2026-06-05

AI Technical Summary

Technical Problem

Existing image recommendation methods struggle to dynamically respond to real-time changes in user behavior, resulting in insufficient relevance and accuracy of recommendation results, which negatively impacts user experience and device usage frequency.

Method used

By acquiring image features and user behavior features of the target image, feature fusion is performed to generate fused features. The current recommendation algorithm is then used for image recommendation processing, while a preset random number generator is used to dynamically adjust the image recommendation list.

Benefits of technology

It improves the accuracy of the recommendation algorithm and the diversity of the image recommendation list, thereby increasing the frequency of user use and the efficiency of device usage.

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Abstract

An embodiment of the present application provides an image recommendation method, which comprises the following steps: obtaining an image feature of a target image and a behavior feature of a user for the target image; performing feature fusion processing based on the image feature and the behavior feature to obtain a fusion feature; providing the fusion feature to a recommendation algorithm at a current time for image recommendation processing to obtain an image recommendation list; performing adjustment processing on the image recommendation list based on a preset random number generator to obtain a recommended image; and providing the recommended image to the user. The behavior feature of the user and the feature of the target image can be fully combined, the accuracy of the recommendation algorithm can be effectively improved, the image recommendation list can be optimized through a dynamic adjustment mechanism, and the use frequency of the user and the use efficiency of the device can be improved.
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