Information recommendation method and device, electronic equipment, computer readable storage medium and computer program product
By acquiring the multimodal feature vectors of the target object and candidate objects, performing dimensionality reduction and attention encoding, and extracting the output vectors of individual and group interests, the problem of low recommendation accuracy and fit in existing technologies is solved, and more accurate information recommendation is achieved.
CN120929666APending Publication Date: 2025-11-11TENCENT TECHNOLOGY (SHENZHEN) CO LTD
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Patent Information
- Application Number
- CN202410574131.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-05-09
- Publication Date
- 2025-11-11
AI Technical Summary
Technical Problem
Existing technologies for information recommendation suffer from limitations in the features they use, resulting in low accuracy and relevance, and failing to effectively combine the individual and group interests of the target audience.
Method used
By acquiring the multimodal feature vectors of the target object and candidate objects, performing dimensionality reduction and attention encoding, extracting the output vectors of individual interest and group interest, and combining information from multiple dimensions to determine recommendation parameters, the target recommendation object is selected.
Benefits of technology
It improves the accuracy and relevance of information recommendations, meeting the multi-dimensional interest needs of the target audience.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention provides an information recommendation method and device, electronic equipment, a computer readable storage medium and a computer program product. The method comprises the steps of obtaining a vector combination; performing dimension reduction based on the vector combination to obtain a first output vector; performing attention coding based on the first multi-modal feature vector to obtain a first weight coefficient set corresponding to the first multi-modal vector, and determining a second output vector representing the individual interest of the target object based on the first weight coefficient set; performing feature extraction on the first multi-modal feature vector to obtain a third output vector representing the group interest of the group to which the target object belongs; determining recommendation parameters based on the first output vector, the second output vector and the third output vector; and determining a target recommendation object for the target object from the plurality of candidate objects based on the plurality of recommendation parameters corresponding to the plurality of candidate objects. According to the method and the device, the target recommendation object can be determined from multiple dimensions, and the recommendation accuracy is improved.
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