Neural Multi-Task Learning for Citation Function and Provenance
2019 ACM/IEEE Joint Conference on Digital Libraries (JCDL)
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sg-nus-scholar.10635-1571272024-04-25T06:17:57Z Neural Multi-Task Learning for Citation Function and Provenance Kan Min-Yen Prasad, Animesh Su, Xuan Sugiyama, Kazunari DEPARTMENT OF COMPUTER SCIENCE INST FOR APPLN OF LEARNING SCI & ED TECH Citation analysis Multi-Task Learning Neural Networks 2019 ACM/IEEE Joint Conference on Digital Libraries (JCDL) 2019-June 394-395 United States 2019-07-29T01:32:44Z 2019-07-29T01:32:44Z 2019-06-02 2019-07-27T08:49:46Z Conference Paper Kan Min-Yen, Prasad, Animesh, Su, Xuan, Sugiyama, Kazunari (2019-06-02). Neural Multi-Task Learning for Citation Function and Provenance. 2019 ACM/IEEE Joint Conference on Digital Libraries (JCDL) 2019-June : 394-395. ScholarBank@NUS Repository. 9781728115474 1552-5996 https://scholarbank.nus.edu.sg/handle/10635/157127 IEEE Elements |
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Citation analysis Multi-Task Learning Neural Networks |
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Citation analysis Multi-Task Learning Neural Networks Kan Min-Yen Prasad, Animesh Su, Xuan Sugiyama, Kazunari Neural Multi-Task Learning for Citation Function and Provenance |
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2019 ACM/IEEE Joint Conference on Digital Libraries (JCDL) |
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DEPARTMENT OF COMPUTER SCIENCE |
author_facet |
DEPARTMENT OF COMPUTER SCIENCE Kan Min-Yen Prasad, Animesh Su, Xuan Sugiyama, Kazunari |
format |
Conference or Workshop Item |
author |
Kan Min-Yen Prasad, Animesh Su, Xuan Sugiyama, Kazunari |
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Kan Min-Yen |
title |
Neural Multi-Task Learning for Citation Function and Provenance |
title_short |
Neural Multi-Task Learning for Citation Function and Provenance |
title_full |
Neural Multi-Task Learning for Citation Function and Provenance |
title_fullStr |
Neural Multi-Task Learning for Citation Function and Provenance |
title_full_unstemmed |
Neural Multi-Task Learning for Citation Function and Provenance |
title_sort |
neural multi-task learning for citation function and provenance |
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IEEE |
publishDate |
2019 |
url |
https://scholarbank.nus.edu.sg/handle/10635/157127 |
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1800913678191558656 |