Constraint-based Pattern Mining

Constraint-Based Pattern Mining is a type of frequent pattern mining approach that incorporates user-specified constraints to guide the discovery process by pruning the search space and focusing on patterns that satisfy predefined conditions.

186

Publications

13K

Citations

357

Authors

177

Institutions

Publications per year

2017–2026

30

Authors

357

  1. JH
    Jiawei Han

    University of Illinois Urbana-Champaign, United States

    13 publications · 2.4K citations

    12

    h-index

  2. LV
    Laks V. S. Lakshmanan

    University of British Columbia, Canada

    11 publications · 1.9K citations

    11

    h-index

  3. CK
    Carson K. Leung

    University of Manitoba, Canada

    12 publications · 606 citations

    11

    h-index

  4. FB
    Francesco Bonchi

    Yahoo (Spain), Spain

    9 publications · 379 citations

    9

    h-index

  5. RT
    Raymond T. Ng

    University of British Columbia, Canada

    8 publications · 1.3K citations

    8

    h-index

1–5 of 357

Venues

  1. Data Mining and Knowledge Discovery

    8 publications · 824 citations

    8

    h-index

  2. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 7 publications · 943 citations

    7

    h-index

  3. Knowledge and Information Systems

    6 publications · 240 citations

    6

    h-index

  4. Applied Intelligence

    6 publications · 105 citations

    6

    h-index

  5. Information Sciences

    6 publications · 410 citations

    6

    h-index

1–5