Intent Classification
Intent Classification is a machine learning task within natural language understanding that assigns a user's utterance in a dialogue system to a specific semantic category representing the underlying goal or intention, thereby enabling the system to generate contextually appropriate responses.
265
Publications
12.8K
Citations
1K
Authors
314
Institutions
Publications per year
2017–2026
201
Variants
Intent Identification
265
Slot-Gated Modeling for Joint Slot Filling and Intent Prediction
Chih-Wen Goo, Guang Gao, Yun-Kai Hsu et al. · 2018 · 520 citations · Full text
BERT for Joint Intent Classification and Slot Filling
Chen Qian, Zhuo Zhu, Wen Wang · arXiv (Cornell University) · 2019 · 412 citations · Full text
Learning query intent from regularized click graphs
Xiao Li, Ye‐Yi Wang, Alex Acero · 2008 · 335 citations
1–5 of 265
1K
7
h-index
6
h-index
3
h-index
3
h-index
3
h-index
1–5 of 1K
314
Microsoft (United States)
Redmond, United States
10 h-index
37 publications
3.2K citations
Amazon (United States)
Seattle, United States
7 h-index
43 publications
2.2K citations
Tsinghua University
Beijing, China
6 h-index
17 publications
874 citations
Google (United States)
Mountain View, United States
5 h-index
27 publications
1.9K citations

Peking University
Beijing, China
5 h-index
12 publications
728 citations
IBM (United States)
Armonk, United States
4 h-index
18 publications
2.5K citations
University of California, Los Angeles
Los Angeles, United States
4 h-index
5 publications
181 citations
Microsoft Research (United Kingdom)
Cambridge, United Kingdom
4 h-index
12 publications
482 citations
1–8 of 314
Repository · 21 publications · 1K citations
14
h-index
Conference · 9 publications · 421 citations
9
h-index
6 publications · 298 citations
6
h-index
3 publications · 89 citations
3
h-index
Conference · 3 publications · 106 citations
3
h-index
1–5