Spatial Rule Learning

Spatial Rule Learning is a data mining methodology that identifies implicit, significant spatial relationships and patterns from geospatial data by deriving rules that characterize the spatial dependencies, proximities, or interactions among geographic entities.

15

Publications

526

Citations

48

Authors

27

Institutions

Publications per year

2017–2026

3

Authors

48

  1. SB
    Stephen B. Fountain

    Kent State University, United States

    2 publications · 31 citations

    2

    h-index

  2. HB
    Hexiang Bai

    Shanxi University, China

    2 publications · 82 citations

    2

    h-index

  3. YG
    Yong Ge

    Institute of Geographic Sciences and Natural Resources Research, China

    2 publications · 82 citations

    2

    h-index

  4. JW
    Jinfeng Wang

    Chinese Academy of Sciences, China

    2 publications · 82 citations

    2

    h-index

  5. MM
    Mortimer Mishkin

    National Institute of Mental Health, United States

    1 publications · 36 citations

    1

    h-index

1–5 of 48

Venues

  1. 1

    h-index

  2. Landscape and Urban Planning

    1 publications · 24 citations

    1

    h-index

  3. 1

    h-index

  4. Knowledge-Based Systems

    1 publications · 46 citations

    1

    h-index

  5. PLoS ONE

    1 publications · 43 citations

    1

    h-index

1–5