US Patent Application 18214323. RECOMMENDED CONTENT SELECTION METHOD AND APPARATUS, DEVICE, STORAGE MEDIUM, AND PROGRAM PRODUCT simplified abstract
Contents
RECOMMENDED CONTENT SELECTION METHOD AND APPARATUS, DEVICE, STORAGE MEDIUM, AND PROGRAM PRODUCT
Organization Name
TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED
Inventor(s)
RECOMMENDED CONTENT SELECTION METHOD AND APPARATUS, DEVICE, STORAGE MEDIUM, AND PROGRAM PRODUCT - A simplified explanation of the abstract
This abstract first appeared for US patent application 18214323 titled 'RECOMMENDED CONTENT SELECTION METHOD AND APPARATUS, DEVICE, STORAGE MEDIUM, AND PROGRAM PRODUCT
Simplified Explanation
- The patent application describes a method performed by a computer device for recommending content to users. - The method involves obtaining an input structure graph that represents associations between user nodes and content nodes. - Fusion vectors are generated for each node in the input structure graph using an interactive prediction model. - A fusion vector for a target node combines feature information of the target node with feature information of another node associated with it. - Interactive prediction values between a target user node and multiple content nodes are determined based on the fusion vectors. - A recommended content node is selected from the multiple content nodes based on the interactive prediction values and a diversity index of the recommended content node set.
Original Abstract Submitted
A recommended content selection method is performed by a computer device. The method includes: obtaining an input structure graph for representing associations between user nodes and content nodes; generating fusion vectors corresponding to nodes in the input structure graph using an interactive prediction model, a fusion vector corresponding to a target node integrates feature information of the target node and feature information of another node associated with the target node; determining, for a target user node, interactive prediction values between the target user node and the plurality of content nodes based on a fusion vector corresponding to the target user node and fusion vectors corresponding to the plurality of content nodes; and selecting a recommended content node from the plurality of content nodes according to the interactive prediction values between the target user node and the plurality of content nodes and a diversity index of a recommended content node set.
