@inproceedings{li-lioma-2022-template,
title = "Template-based Contact Email Generation for Job Recommendation",
author = "Li, Qiuchi and
Lioma, Christina",
editor = "Bosselut, Antoine and
Chandu, Khyathi and
Dhole, Kaustubh and
Gangal, Varun and
Gehrmann, Sebastian and
Jernite, Yacine and
Novikova, Jekaterina and
Perez-Beltrachini, Laura",
booktitle = "Proceedings of the 2nd Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates (Hybrid)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.gem-1.15",
doi = "10.18653/v1/2022.gem-1.15",
pages = "189--197",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Template-based Contact Email Generation for Job Recommendation
%A Li, Qiuchi
%A Lioma, Christina
%Y Bosselut, Antoine
%Y Chandu, Khyathi
%Y Dhole, Kaustubh
%Y Gangal, Varun
%Y Gehrmann, Sebastian
%Y Jernite, Yacine
%Y Novikova, Jekaterina
%Y Perez-Beltrachini, Laura
%S Proceedings of the 2nd Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)
%D 2022
%8 December
%I Association for Computational Linguistics
%C Abu Dhabi, United Arab Emirates (Hybrid)
%F li-lioma-2022-template
%X 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.
%R 10.18653/v1/2022.gem-1.15
%U https://aclanthology.org/2022.gem-1.15
%U https://doi.org/10.18653/v1/2022.gem-1.15
%P 189-197
Markdown (Informal)
[Template-based Contact Email Generation for Job Recommendation](https://aclanthology.org/2022.gem-1.15) (Li & Lioma, GEM 2022)
ACL