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Functional department recruitment system and device based on machine learning and medium

A machine learning and functional technology, applied in the computer field, can solve problems such as affecting the overall employment evaluation of candidates, information asymmetry, and unfair scoring by examiners

Pending Publication Date: 2020-10-27
福建亿能达信息技术股份有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although this method is scientific to a certain extent, it also has the following disadvantages: 1. In the interview process, the examiner often has information asymmetry and cognitive blind spots and deviations when facing the applicants. , it is easy to produce subjective bias; 2. There are many indicators for evaluating the overall quality of the applicant in the interview process, and the weighted average is the total score of the examiner, which makes it difficult to evaluate the overall performance of the applicant more accurately, which in turn affects the overall evaluation of the applicant ;3. The examiner may make unfair scores due to accepting bribes; 4. The examiner needs to score each candidate during the interview, and then calculate the weighted average of the scores after the interview, which is inefficient

Method used

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  • Functional department recruitment system and device based on machine learning and medium
  • Functional department recruitment system and device based on machine learning and medium
  • Functional department recruitment system and device based on machine learning and medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0035] This embodiment provides a machine learning-based recruitment system for functional departments, such as Figure 1 to Figure 2 As shown, the following modules are included:

[0036] The initialization module is used to create a database, a scoring rule and several scoring keywords on the server side, and obtain historical recruitment data; the scoring keywords, such as major scientific research projects, project leaders, first authors, SCI papers , intermediate professional title, clinical experience, strong communication skills, etc.

[0037] The machine learning module is used for the server to use machine learning technology to train the scoring keywords, historical recruitment data and scoring rules to obtain a scoring model;

[0038] A scoring result generation module, used for the server to obtain the latest recruitment data through the client, and use the scoring model to score the latest recruitment data to generate scoring results;

[0039] The scoring result...

Embodiment 2

[0060] This embodiment provides a machine learning-based recruitment device for functional departments, such as image 3 As shown, it includes a memory, a processor, and a computer program stored in the memory and operable on the processor. When the processor executes the computer program, any implementation manner in Embodiment 1 can be realized.

[0061] Since the equipment introduced in this embodiment is the equipment used to implement the system in Embodiment 1 of this application, based on the system introduced in Embodiment 1 of this application, those skilled in the art can understand the specific implementation of the equipment in this embodiment Ways and various variations thereof, so how the device implements the method in the embodiment of the present application will not be described in detail here. As long as those skilled in the art implement the devices used by the system in the embodiments of the present application, they all belong to the intended protection ...

Embodiment 3

[0064] This embodiment provides a machine learning-based recruitment medium for functional departments, such as Figure 4 As shown, a computer program is stored thereon, and when the computer program is executed by a processor, any implementation manner in the first embodiment can be realized.

[0065] The technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0066] Create scoring rules and scoring keywords through the server, and obtain historical recruitment data, and then use machine learning technology on the server to train the scoring keywords, historical recruitment data, and scoring rules to obtain a scoring model, and then use the scoring model to evaluate the latest Scoring the recruitment data overcomes the subjective bias of the examiners, and scoring based on the scoring keywords can also more accurately evaluate the overall performance of the applicants, which ultimately greatly i...

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Abstract

The invention provides a functional department recruitment system and device based on machine learning and a medium in the field of computers, and the system comprises: an initialization module whichis used for creating a database, a scoring rule and a plurality of score keywords at a server, and obtaining historical recruitment data; the machine learning module that is used for the server to train the score keywords, the historical recruitment data and the scoring rules by using a machine learning technology to obtain a score model; the scoring result generation module that is used for the server to obtain the latest recruitment data through the client and score the latest recruitment data by using the scoring model to generate a scoring result; and the scoring result storage module thatis used for storing the scoring result and the latest recruitment data in a database by the server and sending the scoring result to the client through an HTTP protocol. The invention has the advantages that the fairness, rationality and efficiency of recruitment are greatly improved.

Description

technical field [0001] The invention relates to the field of computers, in particular to a machine learning-based recruitment system, equipment and media for functional departments. Background technique [0002] At present, the recruitment of functional departments of the hospital mostly adopts written examination screening, interview inspection and other links to examine candidates, and uses the weighted average method to calculate the comprehensive scores of the candidates in the written examination and interview links, and finally decides the recruitment decision of the candidates according to the order of the comprehensive scores. Although this method is scientific to a certain extent, it also has the following disadvantages: 1. In the interview process, the examiner often has information asymmetry and cognitive blind spots and deviations when facing the applicants. , it is easy to produce subjective bias; 2. There are many indicators for evaluating the overall quality o...

Claims

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Application Information

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IPC IPC(8): G06F21/60G06F21/62G06F21/64G06F40/30G06Q10/10G06K9/62G06N20/00
CPCG06Q10/1053G06F40/30G06F21/602G06F21/6218G06F21/64G06N20/00G06F18/214
Inventor 黄家昌刘远芳陈杜添
Owner 福建亿能达信息技术股份有限公司
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