RiSER: Learning Better Representations for Richly Structured Emails-Reference-Cited by-同舟云学术

RiSER: Learning Better Representations for Richly Structured Emails

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:The World Wide Web Conference on - WWW '19
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Author:

Kocayusufoglu Furkan¹,Sheng Ying²,Vo Nguyen²,Wendt James²,Zhao Qi²,Tata Sandeep²,Najork Marc²

Affiliation:

1. UC Santa Barbara, USA

2. Google, USA

Publisher

ACM Press

Reference50 articles.

1. Douglas Aberdeen, Ondrej Pacovsky, and Andrew Slater. 2010. The learning behind Gmail priority inbox. In LCCC: NIPS 2010 Workshop on Learning on Cores, Clusters and Clouds.

2. Manoj K Agarwal and Jitendra Singh. 2018. Template Trees: Extracting Actionable Information from Machine Generated Emails. In Proceedings of the 30th International Conference on Database and Expert Systems Applications(DEXA). 3-18.

3. Nir Ailon, Zohar S Karnin, Edo Liberty, and Yoelle Maarek. 2013. Threading machine generated email. In Proceedings of the 6th ACM International Conference on Web Search and Data Mining(WSDM). 405-414.

4. Noa Avigdor-Elgrabli, Mark Cwalinski, Dotan Di Castro, Iftah Gamzu, Irena Grabovitch-Zuyev, Liane Lewin-Eytan, and Yoelle Maarek. 2016. Structural clustering of machine-generated mail. In Proceedings of the 25th ACM International on Conference on Information and Knowledge Management(CIKM). 217-226.

5. Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014. Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473(2014).

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