publication . Conference object . Preprint . Other literature type . 2019

This Email Could Save Your Life: Introducing the Task of Email Subject Line Generation

Zhang, Rui; Tetreault, Joel;
Open Access
  • Published: 08 Jun 2019
  • Publisher: Association for Computational Linguistics
Abstract
Given the overwhelming number of emails, an effective subject line becomes essential to better inform the recipient of the email's content. In this paper, we propose and study the task of email subject line generation: automatically generating an email subject line from the email body. We create the first dataset for this task and find that email subject line generation favor extremely abstractive summary which differentiates it from news headline generation or news single document summarization. We then develop a novel deep learning method and compare it to several baselines as well as recent state-of-the-art text summarization systems. We also investigate the ...
Subjects
free text keywords: Natural language processing, computer.software_genre, computer, Computer science, World Wide Web, Artificial intelligence, business.industry, business, Computer Science - Computation and Language
Communities
Digital Humanities and Cultural Heritage
56 references, page 1 of 4

Sakhar Alkhereyf and Owen Rambow. 2017. Work hard, play hard: Email classification on the avocado and enron corpora. In Proceedings of TextGraphs11: the Workshop on Graph-based Methods for Natural Language Processing. [OpenAIRE]

Dzmitry Bahdanau, Philemon Brakel, Kelvin Xu, Anirudh Goyal, Ryan Lowe, Joelle Pineau, Aaron Courville, and Yoshua Bengio. 2017. An actor-critic algorithm for sequence prediction. In ICLR.

Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015. Neural machine translation by jointly learning to align and translate. In ICLR.

Paul N Bennett and Jaime Carbonell. 2005. Detecting action-items in e-mail. In SIGIR.

Giuseppe Carenini, Raymond T Ng, and Xiaodong Zhou. 2007. Summarizing email conversations with clue words. In WWW. [OpenAIRE]

Giuseppe Carenini, Raymond T Ng, and Xiaodong Zhou. 2008. Summarizing emails with conversational cohesion and subjectivity. ACL.

Yen-Chun Chen and Mohit Bansal. 2018. Fast abstractive summarization with reinforce-selected sentence rewriting. In ACL.

Jianpeng Cheng and Mirella Lapata. 2016. Neural summarization by extracting sentences and words. In ACL. [OpenAIRE]

Simon Corston-Oliver, Eric Ringger, Michael Gamon, and Richard Campbell. 2004. Task-focused summarization of email. Text Summarization Branches Out.

Michael Denkowski and Alon Lavie. 2014. Meteor universal: Language specific translation evaluation for any target language. In Proceedings of the ninth workshop on statistical machine translation. [OpenAIRE]

Mark Dredze, Hanna M Wallach, Danny Puller, and Fernando Pereira. 2008. Generating summary keywords for emails using topics. In Proceedings of the 13th international conference on Intelligent user interfaces, pages 199-206. ACM. [OpenAIRE]

Gu¨nes Erkan and Dragomir R Radev. 2004. Lexrank: Graph-based lexical centrality as salience in text summarization. journal of artificial intelligence research, 22:457-479.

Katja Filippova. 2010. Multi-sentence compression: Finding shortest paths in word graphs. In COLING.

Sepp Hochreiter and Ju¨rgen Schmidhuber. 1997. Long short-term memory. Neural computation, 9(8):1735-1780.

Wan-Ting Hsu, Chieh-Kai Lin, Ming-Ying Lee, Kerui Min, Jing Tang, and Min Sun. 2018. A unified model for extractive and abstractive summarization using inconsistency loss. In ACL.

56 references, page 1 of 4
Abstract
Given the overwhelming number of emails, an effective subject line becomes essential to better inform the recipient of the email's content. In this paper, we propose and study the task of email subject line generation: automatically generating an email subject line from the email body. We create the first dataset for this task and find that email subject line generation favor extremely abstractive summary which differentiates it from news headline generation or news single document summarization. We then develop a novel deep learning method and compare it to several baselines as well as recent state-of-the-art text summarization systems. We also investigate the ...
Subjects
free text keywords: Natural language processing, computer.software_genre, computer, Computer science, World Wide Web, Artificial intelligence, business.industry, business, Computer Science - Computation and Language
Communities
Digital Humanities and Cultural Heritage
56 references, page 1 of 4

Sakhar Alkhereyf and Owen Rambow. 2017. Work hard, play hard: Email classification on the avocado and enron corpora. In Proceedings of TextGraphs11: the Workshop on Graph-based Methods for Natural Language Processing. [OpenAIRE]

Dzmitry Bahdanau, Philemon Brakel, Kelvin Xu, Anirudh Goyal, Ryan Lowe, Joelle Pineau, Aaron Courville, and Yoshua Bengio. 2017. An actor-critic algorithm for sequence prediction. In ICLR.

Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015. Neural machine translation by jointly learning to align and translate. In ICLR.

Paul N Bennett and Jaime Carbonell. 2005. Detecting action-items in e-mail. In SIGIR.

Giuseppe Carenini, Raymond T Ng, and Xiaodong Zhou. 2007. Summarizing email conversations with clue words. In WWW. [OpenAIRE]

Giuseppe Carenini, Raymond T Ng, and Xiaodong Zhou. 2008. Summarizing emails with conversational cohesion and subjectivity. ACL.

Yen-Chun Chen and Mohit Bansal. 2018. Fast abstractive summarization with reinforce-selected sentence rewriting. In ACL.

Jianpeng Cheng and Mirella Lapata. 2016. Neural summarization by extracting sentences and words. In ACL. [OpenAIRE]

Simon Corston-Oliver, Eric Ringger, Michael Gamon, and Richard Campbell. 2004. Task-focused summarization of email. Text Summarization Branches Out.

Michael Denkowski and Alon Lavie. 2014. Meteor universal: Language specific translation evaluation for any target language. In Proceedings of the ninth workshop on statistical machine translation. [OpenAIRE]

Mark Dredze, Hanna M Wallach, Danny Puller, and Fernando Pereira. 2008. Generating summary keywords for emails using topics. In Proceedings of the 13th international conference on Intelligent user interfaces, pages 199-206. ACM. [OpenAIRE]

Gu¨nes Erkan and Dragomir R Radev. 2004. Lexrank: Graph-based lexical centrality as salience in text summarization. journal of artificial intelligence research, 22:457-479.

Katja Filippova. 2010. Multi-sentence compression: Finding shortest paths in word graphs. In COLING.

Sepp Hochreiter and Ju¨rgen Schmidhuber. 1997. Long short-term memory. Neural computation, 9(8):1735-1780.

Wan-Ting Hsu, Chieh-Kai Lin, Ming-Ying Lee, Kerui Min, Jing Tang, and Min Sun. 2018. A unified model for extractive and abstractive summarization using inconsistency loss. In ACL.

56 references, page 1 of 4
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publication . Conference object . Preprint . Other literature type . 2019

This Email Could Save Your Life: Introducing the Task of Email Subject Line Generation

Zhang, Rui; Tetreault, Joel;