Resume Named Entity Recognition Method and System

A named entity recognition and named entity technology, applied in neural learning methods, instruments, semantic tool creation and other directions, can solve problems such as reducing the amount of calculation, unable to obtain bidirectional information of sentences, increasing the data volume of training sets, etc., to achieve enhanced semantic representation , improve the accuracy of label prediction and improve the efficiency of information recognition

Active Publication Date: 2022-06-21
SHANDONG NORMAL UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Chinese invention patent (application number: CN109800437A, patent name: a named entity recognition method based on feature fusion), through feature fusion after extracting feature semantics, word features, and character features, classify entity information and improve named entity classification accuracy and reduce the amount of calculation, but due to the adoption of the LSTM network, the two-way information of the sentence cannot be obtained. Although the amount of calculation is saved, the data volume requirement for the training set is increased at the same time.

Method used

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  • Resume Named Entity Recognition Method and System
  • Resume Named Entity Recognition Method and System
  • Resume Named Entity Recognition Method and System

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0049] This embodiment provides a resume named entity recognition method;

[0050] like figure 1 As shown, resume named entity recognition methods, including:

[0051] S101: Obtain the pending resume;

[0052] S102: Preprocess the resume to be processed;

[0053] S103: Match the preprocessed resume with the entities in the custom entity dictionary library one by one to obtain a first predicted named entity set that is successfully matched; wherein, the first predicted named entity set includes: several named entities;

[0054] S104: Input the preprocessed resume into the trained resume named entity recognition model to obtain a second predicted named entity set; wherein, the second predicted named entity set includes: several named entities; the resume named entity recognition model , including: BiLSTM model and conditional random field model CRF connected to each other;

[0055] S105: Take a union of the first predicted named entity set and the second predicted named enti...

Embodiment 2

[0154] This embodiment provides a resume named entity recognition system;

[0155] Resume named entity recognition system, including:

[0156] an acquisition module, which is configured to: acquire pending resumes;

[0157] a preprocessing module, which is configured to: preprocess the resume to be processed;

[0158] The matching module is configured to: match the preprocessed resume with the entities in the custom entity dictionary library one by one to obtain the first predicted named entity set that is successfully matched; wherein, the first predicted named entity set includes: several named entities;

[0159] The prediction module is configured to: input the preprocessed resume into the trained resume named entity recognition model to obtain a second predicted named entity set; wherein, the second predicted named entity set includes: several named entities ;CV named entity recognition model, including: BiLSTM model and conditional random field model CRF connected to e...

Embodiment 3

[0166] This embodiment also provides an electronic device, including: one or more processors, one or more memories, and one or more computer programs; wherein the processor is connected to the memory, and the one or more computer programs are Stored in the memory, when the electronic device runs, the processor executes one or more computer programs stored in the memory, so that the electronic device executes the method described in the first embodiment.

[0167] It should be understood that, in this embodiment, the processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors, DSPs, application-specific integrated circuits (ASICs), off-the-shelf programmable gate arrays (FPGAs), or other programmable logic devices. , discrete gate or transistor logic devices, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or th...

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Abstract

The invention discloses a resume named entity recognition method and system, comprising: acquiring resumes to be processed; preprocessing the resumes to be processed; matching the preprocessed resumes with entities in a self-defined entity dictionary library one by one to obtain matching The successful first predicted named entity set; input the preprocessed resume into the trained resume named entity recognition model to obtain the second predicted named entity set; for the first predicted named entity set and the second predicted named entity set Take the union to obtain the merged predicted named entity set; use the named entities in the merged predicted named entity set as the final named entity recognition result of the resume to be processed; generate knowledge based on the final named entity recognition result of the resume to be processed Atlas. Display and store data in a more novel way, and provide help for resume information labeling.

Description

technical field [0001] The present invention relates to the technical field of machine learning and knowledge graph, in particular to a method and system for identifying a resume named entity. Background technique [0002] The statements in this section merely provide background related to the present disclosure and do not necessarily constitute prior art. [0003] In recent years, with the rapid increase of graduates and the increasing number of resumes, the efficiency issue has attracted more and more attention. Some large and medium-sized companies have received hundreds or even thousands of resumes. It will take a lot of time and energy to find out what kind of ability a candidate has in a resume. If you can mark the award-winning experience and internship experience in the resume, Form a visual resume, it will be very convenient to consult. [0004] Chinese invention patent (application number: CN109800437A, patent name: a named entity recognition method based on feat...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F40/295G06F40/284G06F16/36G06F40/205G06F40/242G06F16/335G06F16/35G06N3/04G06N3/08
CPCG06F40/295G06F40/284G06F40/242G06F40/205G06F16/367G06F16/335G06F16/355G06N3/08G06N3/044
Inventor 闫伟宋澳东张亮姜新泉隋远褚力宁胡晴
Owner SHANDONG NORMAL UNIV
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