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

Authors

1K

  1. GT
    Gökhan Tür

    SRI International, United States

    7 publications · 402 citations

    7

    h-index

  2. DH
    Dilek Hakkani‐Tür

    Microsoft (United States), United States

    6 publications · 338 citations

    6

    h-index

  3. BZ
    Bowen Zhou

    IBM (United States), United States

    3 publications · 273 citations

    3

    h-index

  4. PJ
    Ping Jian

    Beijing Institute of Technology, China

    3 publications · 236 citations

    3

    h-index

  5. JS
    Jian Sun

    Beijing Institute of Technology, China

    3 publications · 236 citations

    3

    h-index

1–5 of 1K

Venues

  1. arXiv (Cornell University)

    Repository · 21 publications · 1K citations

    14

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 9 publications · 421 citations

    9

    h-index

  3. IEEE Access

    6 publications · 298 citations

    6

    h-index

  4. Knowledge-Based Systems

    3 publications · 89 citations

    3

    h-index

  5. 3

    h-index

1–5