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Resource recommendation method, graph convolutional neural network model training method and equipment

A convolutional neural network and recommendation method technology, which is applied in the field of graph convolutional neural network model training methods and equipment, and resource recommendation methods, can solve problems such as increasing difficulty, and achieve the effect of improving user experience and high accuracy of resource recommendation

Pending Publication Date: 2022-04-29
上海携旅信息技术有限公司
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Problems solved by technology

In this case, the overload of information resources increases the difficulty for users to independently select the content of interest.

Method used

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  • Resource recommendation method, graph convolutional neural network model training method and equipment
  • Resource recommendation method, graph convolutional neural network model training method and equipment
  • Resource recommendation method, graph convolutional neural network model training method and equipment

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Embodiment Construction

[0052] Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art.

[0053] The drawings are merely schematic illustrations of the invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus repeated descriptions thereof will be omitted. Some of the block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software, or in one or more hardware forwarding modules or integrated circuits, or in different networks and / or pro...

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Abstract

The invention provides a resource recommendation method, a graph convolutional neural network model training method and equipment, and the method comprises the steps: obtaining a graph convolutional neural network model corresponding to a target user under the condition that the information of candidate resources is obtained in response to the input of the target user, inputting the information of the candidate resources into the graph convolutional neural network model, and carrying out the training of the candidate resources. And in the graph convolutional neural network model, predicting at least one level of node by taking the information of the candidate resource as a starting node until the information of the recommended resource is output, and sending the information of the recommended resource to the client, the node being a resource attribute feature or a resource node. According to the method, the graph convolutional neural network model is adopted for node prediction, so that the recommended resources can be predicted step by step according to the candidate resources, and compared with an existing traversal query scheme adopting a knowledge graph, the recommended resources can more accurately reflect the interest of the user, the resource recommendation accuracy is high, and the user experience is improved.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to a resource recommendation method, a graph convolutional neural network model training method and equipment. Background technique [0002] With the rapid development of the Internet, the amount of data is increasing exponentially. In this case, the overload of information resources increases the difficulty for users to independently select the content they are interested in. Therefore, the prior art proposes a solution of recommending resources to a user terminal, so as to improve user experience. [0003] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of the present invention, and therefore may include information that does not constitute prior art known to those of ordinary skill in the art. Contents of the invention [0004] In view of the problems in the prior art, the purpose ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/9535G06F16/9538G06N3/04G06N3/08
CPCG06F16/9535G06F16/9538G06N3/08G06N3/045
Inventor 王荣生程婉玉李健
Owner 上海携旅信息技术有限公司
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