research-article

An Interactive Neural Network Approach to Keyphrase Extraction in Talent Recruitment

Authors:

Jingshuai Zhang,

Hui XiongAuthors Info & Claims

CIKM '21: Proceedings of the 30th ACM International Conference on Information & Knowledge Management

Pages 2383 - 2393

https://doi.org/10.1145/3459637.3482319

Published: 30 October 2021 Publication History

Abstract

As a fundamental task of document content analysis, keyphrase extraction (KE) aims at predicting a set of lexical units that conveys the core information of the document. In this paper, we study the problem of KE in the talent recruitment. This problem is critical for the development of a variety of intelligent recruitment services, such as person-job fit, market trend analysis and course recommendation. However, unlike traditional textual data, the texts from the recruitment domain, such as resume and job postings, often have unique characteristics of abbreviation and succinctness, resulting in massive keyphrases consisting of inconsecutive words that are hard to be fully captured by existing KE methods. To this end, we propose an interactive neural network approach, INKE, for facilitating KE in the talent recruitment. To be specific, we first introduce a novel keyphrase indicator that captures the explicit hint information for each keyphrase. Then, we design a dynamically-initialized decoder which can generate keyphrases in an interactive manner. Moreover, we propose a hierarchical reinforcement learning algorithm to enhance the interaction between the hint information capture and keyphrase generation. Finally, extensive experiments on real-world data clearly validate the effectiveness and interpretability of INKE compared with state-of-the-art baselines.

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Cited By

Qin CZhu HShen DSun YYao KWang PXiong H(2023)Automatic Skill-Oriented Question Generation and Recommendation for Intelligent Job InterviewsACM Transactions on Information Systems10.1145/360455242:1(1-32)Online publication date: 18-Aug-2023
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Fang CQin CZhang QYao KZhang JZhu HZhuang FXiong HSingh ASun YAkoglu LGunopulos DYan XKumar ROzcan FYe J(2023)RecruitPro: A Pretrained Language Model with Skill-Aware Prompt Learning for Intelligent RecruitmentProceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3580305.3599894(3991-4002)Online publication date: 6-Aug-2023
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Zhu HXiong HGe YLim ESingh ASun YAkoglu LGunopulos DYan XKumar ROzcan FYe J(2023)The 4th International Workshop on Talent and Management Computing (TMC'2023)Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3580305.3599200(5909-5910)Online publication date: 6-Aug-2023
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Index Terms

An Interactive Neural Network Approach to Keyphrase Extraction in Talent Recruitment
1. Information systems
  1. Information retrieval
    1. Document representation

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cover image ACM Conferences

CIKM '21: Proceedings of the 30th ACM International Conference on Information & Knowledge Management

October 2021

4966 pages

ISBN:9781450384469

DOI:10.1145/3459637

General Chairs:
Gianluca Demartini
The University of Queensland, Australia
,
Guido Zuccon
The University of Queensland, Australia
,
Program Chairs:
J. Shane Culpepper
RMIT University, Australia
,
Zi Huang
The University of Queensland, Australia
,
Hanghang Tong
University of Illinois at Urbana-Champaign, USA

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Published: 30 October 2021

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November 1 - 5, 2021

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Cited By

Qin CZhu HShen DSun YYao KWang PXiong H(2023)Automatic Skill-Oriented Question Generation and Recommendation for Intelligent Job InterviewsACM Transactions on Information Systems10.1145/360455242:1(1-32)Online publication date: 18-Aug-2023
https://dl.acm.org/doi/10.1145/3604552
Fang CQin CZhang QYao KZhang JZhu HZhuang FXiong HSingh ASun YAkoglu LGunopulos DYan XKumar ROzcan FYe J(2023)RecruitPro: A Pretrained Language Model with Skill-Aware Prompt Learning for Intelligent RecruitmentProceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3580305.3599894(3991-4002)Online publication date: 6-Aug-2023
https://dl.acm.org/doi/10.1145/3580305.3599894
Zhu HXiong HGe YLim ESingh ASun YAkoglu LGunopulos DYan XKumar ROzcan FYe J(2023)The 4th International Workshop on Talent and Management Computing (TMC'2023)Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3580305.3599200(5909-5910)Online publication date: 6-Aug-2023
https://dl.acm.org/doi/10.1145/3580305.3599200
Yao KZhang JQin CSong XWang PZhu HXiong H(2023)ResuFormer: Semantic Structure Understanding for Resumes via Multi-Modal Pre-training2023 IEEE 39th International Conference on Data Engineering (ICDE)10.1109/ICDE55515.2023.00242(3154-3167)Online publication date: Apr-2023
https://doi.org/10.1109/ICDE55515.2023.00242
Yao KZhang JQin CWang PZhu HXiong H(2022)Knowledge Enhanced Person-Job Fit for Talent Recruitment2022 IEEE 38th International Conference on Data Engineering (ICDE)10.1109/ICDE53745.2022.00325(3467-3480)Online publication date: May-2022
https://doi.org/10.1109/ICDE53745.2022.00325
Yao KWang HQin CZhu HWu YZhang L(undefined)CARL: Unsupervised Code-Based Adversarial Attacks for Programming Language Models via Reinforcement LearningACM Transactions on Software Engineering and Methodology10.1145/3688839
https://dl.acm.org/doi/10.1145/3688839

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