Social network-based recommendation model training method and apparatus

By constructing an object hypergraph in social networks and using encrypted gradient training, the problem of recommendation systems relying on privacy data is solved, achieving personalized recommendations and strong privacy protection.

CN115391638BActive Publication Date: 2026-05-29ZHEJIANG UNIV

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
ZHEJIANG UNIV
Filing Date
2022-07-12
Publication Date
2026-05-29

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Abstract

The application provides a social network-based recommendation model training method and device, wherein the social network-based recommendation model training method comprises the following steps: determining a target user and a reference user cluster of the target user; obtaining local object information of the target user and public object information of the reference user cluster, wherein the public object information is object information disclosed by a reference user; constructing an object hypergraph based on the local object information and the public object information, and determining user preference information of the target user based on the object hypergraph; training a local recommendation model according to the user preference information to obtain a local training gradient, wherein the local training gradient is a model gradient after encryption coding; and uploading the local training gradient to a server, so that the server updates a target recommendation model according to the local training gradient.
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