Neural Sequence Tagging
Neural Sequence Tagging is a neural network–based method for assigning part-of-speech tags to words in a sentence by modeling the sequential dependencies among tokens using architectures such as recurrent neural networks, convolutional neural networks, or transformers.
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1.6K
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90
Authors
39
Institutions
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2017–2026
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Using Context Information for Dialog Act Classification in DNN Framework
Yang Liu, Kun Han, Zhao Tan et al. · 2017 · 103 citations · Full text
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University of Illinois Urbana-Champaign
Urbana, United States
2 h-index
2 publications
96 citations
California Southern University
Chandler, United States
1 h-index
2 publications
156 citations
University of Lisbon
Lisbon, Portugal
1 h-index
1 publications
12 citations
Kaohsiung Medical University
Kaohsiung City, Taiwan
1 h-index
1 publications
11 citations
Toyohashi University of Technology
Toyohashi, Japan
1 h-index
1 publications
13 citations

National Taitung University
Taitung, Taiwan
1 h-index
1 publications
11 citations

National Research University Higher School of Economics
Moscow, Russia
1 h-index
2 publications
20 citations

Beijing Institute of Technology
Beijing, China
1 h-index
1 publications
115 citations
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Repository · 5 publications · 378 citations
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1 publications · 13 citations
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1 publications · 26 citations
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Conference · 1 publications · 115 citations
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1 publications · 11 citations
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