Active Learning For Clustering

Active Learning for Clustering is a machine learning framework that iteratively selects the most informative instances for labeling to improve clustering performance by leveraging human feedback in guiding the formation of data groupings.

81

Publications

5.2K

Citations

254

Authors

116

Institutions

Publications per year

2017–2026

30

Authors

254

  1. SO
    Solange Oliveira Rezende

    Universidade de São Paulo, Brazil

    3 publications · 38 citations

    3

    h-index

  2. RH
    Ruizhang Huang

    Guizhou University, China

    3 publications · 98 citations

    3

    h-index

  3. CF
    Chun-Sung Ferng

    National Taiwan University, Taiwan

    2 publications · 32 citations

    2

    h-index

  4. FM
    Fan Min

    Southwest Petroleum University, China

    2 publications · 161 citations

    2

    h-index

  5. CL
    Chunliang Li

    St. Jude Children's Research Hospital, United States

    2 publications · 32 citations

    2

    h-index

1–5 of 254

Venues

  1. Intelligent Data Analysis

    IDA · 4 publications · 56 citations

    4

    h-index

  2. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 4 publications · 333 citations

    4

    h-index

  3. Expert Systems with Applications

    2 publications · 140 citations

    2

    h-index

  4. Soft Computing

    2 publications · 44 citations

    2

    h-index

  5. Remote Sensing

    2 publications · 74 citations

    2

    h-index

1–5