Multi-label Text Classification
Multi-Label Text Classification is a text classification task in which each document is assigned a subset of multiple non-exclusive labels from a predefined label set, distinguishing it from single-label classification by allowing multiple concurrent category memberships.
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2017–2026
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Grigorios Tsoumakas, Ioannis Katakis · International Journal of Data Warehousing and Mining · 2007 · 2.5K citations
Daniel Ramage, David Hall, Ramesh Nallapati et al. · 2009 · 1.2K citations · Full text
An extensive experimental comparison of methods for multi-label learning
Gjorgji Madjarov, Dragi Kocev, Dejan Gjorgjevikj et al. · Pattern Recognition · 2012 · 731 citations
Deep Learning for Extreme Multi-label Text Classification
Jingzhou Liu, Wei-Cheng Chang, Yuexin Wu et al. · 2017 · 659 citations
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Chinese Academy of Sciences
Beijing, China
14 h-index
32 publications
1.8K citations

Southeast University
Nanjing, China
10 h-index
21 publications
2.5K citations

Peking University
Beijing, China
9 h-index
35 publications
1.9K citations
Carnegie Mellon University
Pittsburgh, United States
9 h-index
20 publications
4K citations
Tencent (China)
Shenzhen, China
9 h-index
34 publications
1.6K citations
Tsinghua University
Beijing, China
9 h-index
18 publications
1.6K citations
University of Illinois Chicago
Chicago, United States
9 h-index
12 publications
555 citations

National Taiwan University
Taipei, Taiwan
8 h-index
15 publications
606 citations
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Repository · 55 publications · 2.4K citations
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17 publications · 1.9K citations
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Conference · 16 publications · 1.6K citations
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