@inproceedings{mukherjee-etal-2020-smart,
title = "Smart To-Do: Automatic Generation of To-Do Items from Emails",
author = "Mukherjee, Sudipto and
Mukherjee, Subhabrata and
Hasegawa, Marcello and
Hassan Awadallah, Ahmed and
White, Ryen",
editor = "Jurafsky, Dan and
Chai, Joyce and
Schluter, Natalie and
Tetreault, Joel",
booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.acl-main.767",
doi = "10.18653/v1/2020.acl-main.767",
pages = "8680--8689",
abstract = "Intelligent features in email service applications aim to increase productivity by helping people organize their folders, compose their emails and respond to pending tasks. In this work, we explore a new application, Smart-To-Do, that helps users with task management over emails. We introduce a new task and dataset for automatically generating To-Do items from emails where the sender has promised to perform an action. We design a two-stage process leveraging recent advances in neural text generation and sequence-to-sequence learning, obtaining BLEU and ROUGE scores of 0.23 and 0.63 for this task. To the best of our knowledge, this is the first work to address the problem of composing To-Do items from emails.",
}
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<abstract>Intelligent features in email service applications aim to increase productivity by helping people organize their folders, compose their emails and respond to pending tasks. In this work, we explore a new application, Smart-To-Do, that helps users with task management over emails. We introduce a new task and dataset for automatically generating To-Do items from emails where the sender has promised to perform an action. We design a two-stage process leveraging recent advances in neural text generation and sequence-to-sequence learning, obtaining BLEU and ROUGE scores of 0.23 and 0.63 for this task. To the best of our knowledge, this is the first work to address the problem of composing To-Do items from emails.</abstract>
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%0 Conference Proceedings
%T Smart To-Do: Automatic Generation of To-Do Items from Emails
%A Mukherjee, Sudipto
%A Mukherjee, Subhabrata
%A Hasegawa, Marcello
%A Hassan Awadallah, Ahmed
%A White, Ryen
%Y Jurafsky, Dan
%Y Chai, Joyce
%Y Schluter, Natalie
%Y Tetreault, Joel
%S Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
%D 2020
%8 July
%I Association for Computational Linguistics
%C Online
%F mukherjee-etal-2020-smart
%X Intelligent features in email service applications aim to increase productivity by helping people organize their folders, compose their emails and respond to pending tasks. In this work, we explore a new application, Smart-To-Do, that helps users with task management over emails. We introduce a new task and dataset for automatically generating To-Do items from emails where the sender has promised to perform an action. We design a two-stage process leveraging recent advances in neural text generation and sequence-to-sequence learning, obtaining BLEU and ROUGE scores of 0.23 and 0.63 for this task. To the best of our knowledge, this is the first work to address the problem of composing To-Do items from emails.
%R 10.18653/v1/2020.acl-main.767
%U https://aclanthology.org/2020.acl-main.767
%U https://doi.org/10.18653/v1/2020.acl-main.767
%P 8680-8689
Markdown (Informal)
[Smart To-Do: Automatic Generation of To-Do Items from Emails](https://aclanthology.org/2020.acl-main.767) (Mukherjee et al., ACL 2020)
ACL
- Sudipto Mukherjee, Subhabrata Mukherjee, Marcello Hasegawa, Ahmed Hassan Awadallah, and Ryen White. 2020. Smart To-Do: Automatic Generation of To-Do Items from Emails. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 8680–8689, Online. Association for Computational Linguistics.