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Post matching method and device based on graph neural network

A technology of neural network and matching method, applied in the field of job matching based on graph neural network, can solve the problem of low matching between recommended jobs and personnel, and achieve the effect of high matching and reasonable jobs

Active Publication Date: 2022-03-11
PEKING UNIV
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Problems solved by technology

[0004] The above method has problems such as the low degree of conformity between the recommended positions and personnel

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  • Post matching method and device based on graph neural network
  • Post matching method and device based on graph neural network
  • Post matching method and device based on graph neural network

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Embodiment Construction

[0045] In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. Obviously, the described embodiments are part of the embodiments of the present invention , but not all examples. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0046] It should be noted that, in the description of the embodiments of the present invention, the terms "comprising", "comprising" or any other variant thereof are intended to cover a non-exclusive inclusion, so that a process, method, article or device comprising a series of elements Not only those elements are included, but also other elements not expressly listed or inherent in such proc...

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Abstract

The invention provides a post matching method and device based on a graph neural network. The method comprises the following steps: acquiring a target job sequence corresponding to a target resume; inputting the target job sequence into a post matching model, and obtaining the matching degree between the target job sequence output by the post matching model and a plurality of preset posts; determining a matching post of the target resume in a plurality of preset posts according to the matching degree; the post matching model is constructed based on a graph neural network; the post matching model is obtained based on the sample job sequence and sample matching posts corresponding to the sample job sequence after training. According to the post matching method and device based on the graph neural network provided by the invention, the post matching model constructed based on the graph neural network is utilized to match the next job of the individual corresponding to the target resume data with the job of each preset post according to the target job sequence, so that the matched posts are more reasonable, and the matching efficiency is improved. And the conformity with personnel is higher.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence, in particular to a job matching method and device based on a graph neural network. Background technique [0002] Most of the existing cadre management systems only have simple functions such as database storage and rule query. [0003] With the development of recommendation system technology, job recommendation is one of the most important application directions of recommendation system. Existing prediction models based on job-seeking text information can map text into a vectorized space and use text classification for job recommendation. [0004] The above method has problems such as the low degree of conformity between the recommended positions and personnel. Contents of the invention [0005] Aiming at the problems existing in the prior art, embodiments of the present invention provide a job matching method and device based on a graph neural network. [0006] The p...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/9035G06N3/04G06N3/08G06Q10/10G06F16/901
CPCG06F16/9035G06Q10/105G06F16/9024G06N3/04G06N3/08Y02P90/30
Inventor 胡文蕙刘学洋张津婵邵文宇
Owner PEKING UNIV
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