Template-based Contact Email Generation for Job Recommendation

Qiuchi Li, Christina Lioma


Abstract
Text generation has long been a popular research topic in NLP. However, the task of generating contact 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.
Anthology ID:
2022.gem-1.15
Volume:
Proceedings of the 2nd Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)
Month:
December
Year:
2022
Address:
Abu Dhabi, United Arab Emirates (Hybrid)
Editors:
Antoine Bosselut, Khyathi Chandu, Kaustubh Dhole, Varun Gangal, Sebastian Gehrmann, Yacine Jernite, Jekaterina Novikova, Laura Perez-Beltrachini
Venue:
GEM
SIG:
SIGGEN
Publisher:
Association for Computational Linguistics
Note:
Pages:
189–197
Language:
URL:
https://aclanthology.org/2022.gem-1.15
DOI:
10.18653/v1/2022.gem-1.15
Bibkey:
Cite (ACL):
Qiuchi Li and Christina Lioma. 2022. Template-based Contact Email Generation for Job Recommendation. In Proceedings of the 2nd Workshop on Natural Language Generation, Evaluation, and Metrics (GEM), pages 189–197, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
Cite (Informal):
Template-based Contact Email Generation for Job Recommendation (Li & Lioma, GEM 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.gem-1.15.pdf
Video:
 https://aclanthology.org/2022.gem-1.15.mp4