Template-based Recruitment Email Generation for Job Recommendation

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Standard

Template-based Recruitment Email Generation for Job Recommendation. / Li, Qiuchi; Lioma, Christina.

GEM 2022 - 2nd Workshop on Natural Language Generation, Evaluation, and Metrics, Proceedings of the Workshop. Association for Computational Linguistics (ACL), 2022. p. 189-197.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Harvard

Li, Q & Lioma, C 2022, Template-based Recruitment Email Generation for Job Recommendation. in GEM 2022 - 2nd Workshop on Natural Language Generation, Evaluation, and Metrics, Proceedings of the Workshop. Association for Computational Linguistics (ACL), pp. 189-197, 2nd Workshop on Natural Language Generation, Evaluation, and Metrics, GEM 2022, as part of EMNLP 2022, Abu Dhabi, United Arab Emirates, 07/12/2022. <https://aclanthology.org/2022.gem-1.15/>

APA

Li, Q., & Lioma, C. (2022). Template-based Recruitment Email Generation for Job Recommendation. In GEM 2022 - 2nd Workshop on Natural Language Generation, Evaluation, and Metrics, Proceedings of the Workshop (pp. 189-197). Association for Computational Linguistics (ACL). https://aclanthology.org/2022.gem-1.15/

Vancouver

Li Q, Lioma C. Template-based Recruitment Email Generation for Job Recommendation. In GEM 2022 - 2nd Workshop on Natural Language Generation, Evaluation, and Metrics, Proceedings of the Workshop. Association for Computational Linguistics (ACL). 2022. p. 189-197

Author

Li, Qiuchi ; Lioma, Christina. / Template-based Recruitment Email Generation for Job Recommendation. GEM 2022 - 2nd Workshop on Natural Language Generation, Evaluation, and Metrics, Proceedings of the Workshop. Association for Computational Linguistics (ACL), 2022. pp. 189-197

Bibtex

@inproceedings{a1a382692a0543a7b6fedd887f46fa78,
title = "Template-based Recruitment Email Generation for Job Recommendation",
abstract = "Text generation has long been a popular research topic in NLP. However, the task of generating recruitment emails from recruiters to candidates in the job recommendation scenario has received little attention by the research community. This work aims at defining the topic of automatic email generation for job recommendation, identifying the challenges, and providing a baseline template-based solution for Danish jobs. Evaluation by human experts shows that our method is effective. We wrap up by discussing the future research directions for better solving this task.",
author = "Qiuchi Li and Christina Lioma",
note = "Publisher Copyright: {\textcopyright} 2022 Association for Computational Linguistics.; 2nd Workshop on Natural Language Generation, Evaluation, and Metrics, GEM 2022, as part of EMNLP 2022 ; Conference date: 07-12-2022",
year = "2022",
language = "English",
pages = "189--197",
booktitle = "GEM 2022 - 2nd Workshop on Natural Language Generation, Evaluation, and Metrics, Proceedings of the Workshop",
publisher = "Association for Computational Linguistics (ACL)",
address = "United States",

}

RIS

TY - GEN

T1 - Template-based Recruitment Email Generation for Job Recommendation

AU - Li, Qiuchi

AU - Lioma, Christina

N1 - Publisher Copyright: © 2022 Association for Computational Linguistics.

PY - 2022

Y1 - 2022

N2 - Text generation has long been a popular research topic in NLP. However, the task of generating recruitment emails from recruiters to candidates in the job recommendation scenario has received little attention by the research community. This work aims at defining the topic of automatic email generation for job recommendation, identifying the challenges, and providing a baseline template-based solution for Danish jobs. Evaluation by human experts shows that our method is effective. We wrap up by discussing the future research directions for better solving this task.

AB - Text generation has long been a popular research topic in NLP. However, the task of generating recruitment emails from recruiters to candidates in the job recommendation scenario has received little attention by the research community. This work aims at defining the topic of automatic email generation for job recommendation, identifying the challenges, and providing a baseline template-based solution for Danish jobs. Evaluation by human experts shows that our method is effective. We wrap up by discussing the future research directions for better solving this task.

UR - http://www.scopus.com/inward/record.url?scp=85152946797&partnerID=8YFLogxK

M3 - Article in proceedings

AN - SCOPUS:85152946797

SP - 189

EP - 197

BT - GEM 2022 - 2nd Workshop on Natural Language Generation, Evaluation, and Metrics, Proceedings of the Workshop

PB - Association for Computational Linguistics (ACL)

T2 - 2nd Workshop on Natural Language Generation, Evaluation, and Metrics, GEM 2022, as part of EMNLP 2022

Y2 - 7 December 2022

ER -

ID: 360401053