research-article

A Deep-Learning-Inspired Person-Job Matching Model Based on Sentence Vectors and Subject-Term Graphs

Authors:

Zhenhong Jiang,

Lingxi Peng Academic Editor:

Zhenyu LuAuthors Info & Claims

Complexity, Volume 2021

https://doi.org/10.1155/2021/6206288

Published: 01 January 2021 Publication History

Abstract

In this study, an end-to-end person-to-job post data matching model is constructed, and the experiments for matching people with the actual recruitment data are conducted. First, the representation of the constructed knowledge in the low-dimensional space is described. Then, it is explained in the Bidirectional Encoder Representations from Transformers (BERT) pretraining language model, which is introduced as the encoding model for textual information. The structure of the person-post matching model is explained in terms of the attention mechanism and its computational layers. Finally, the experiments based on the person-post matching model are compared with a variety of person-post matching methods in the actual recruitment dataset, and the experimental results are analyzed.

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Cited By

Mashayekhi YLi NKang BLijffijt JDe Bie T(2024)A Challenge-based Survey of E-recruitment Recommendation SystemsACM Computing Surveys10.1145/365994256:10(1-33)Online publication date: 22-Jun-2024
https://dl.acm.org/doi/10.1145/3659942
Kamran SHosseini SEsmailzadeh SKangavari MHua W(2024)Cognition2Vocation: meta-learning via ConvNets and continuous transformersNeural Computing and Applications10.1007/s00521-024-09749-036:21(12935-12950)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1007/s00521-024-09749-0
Espinal AHaralambous YBedart DPuentes J(2023)A Quality Assessment Framework for Information Extraction in Job AdvertisementsSN Computer Science10.1007/s42979-023-02247-54:6Online publication date: 12-Oct-2023
https://dl.acm.org/doi/10.1007/s42979-023-02247-5

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Published In

cover image Complexity

Complexity Volume 2021, Issue

2021

20672 pages

ISSN:1076-2787

Issue’s Table of Contents

Copyright © 2021 Xiaowei Wang et al.

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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John Wiley & Sons, Inc.

United States

Publication History

Published: 01 January 2021

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Cited By

Mashayekhi YLi NKang BLijffijt JDe Bie T(2024)A Challenge-based Survey of E-recruitment Recommendation SystemsACM Computing Surveys10.1145/365994256:10(1-33)Online publication date: 22-Jun-2024
https://dl.acm.org/doi/10.1145/3659942
Kamran SHosseini SEsmailzadeh SKangavari MHua W(2024)Cognition2Vocation: meta-learning via ConvNets and continuous transformersNeural Computing and Applications10.1007/s00521-024-09749-036:21(12935-12950)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1007/s00521-024-09749-0
Espinal AHaralambous YBedart DPuentes J(2023)A Quality Assessment Framework for Information Extraction in Job AdvertisementsSN Computer Science10.1007/s42979-023-02247-54:6Online publication date: 12-Oct-2023
https://dl.acm.org/doi/10.1007/s42979-023-02247-5

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