Concepedia

Ordered Itemset Mining

Ordered Itemset Mining is a type of sequential pattern mining that discovers statistically significant itemsets with a specific order of occurrence in transactional databases, distinguishing itself from unordered itemset mining by incorporating temporal or positional precedence among items.

2

Publications

79

Citations

6

Authors

3

Institutions

Publications per year

2017–2026

1

Parents

Publications

2

1–2 of 2

Authors

6

  1. JK
    Jason K. Wang

    Stanford University, United States

    1 publications · 56 citations

    1

    h-index

  2. CJ
    Cong-Rui Ji

    Peking University, China

    1 publications · 23 citations

    1

    h-index

  3. ZD
    Zhi‐Hong Deng

    Peking University, China

    1 publications · 23 citations

    1

    h-index

  4. JH
    Jonathan H. Chen

    Stanford University, United States

    1 publications · 56 citations

    1

    h-index

  5. CS
    Christopher Sharp

    Stanford University, United States

    1 publications · 56 citations

    1

    h-index

1–5 of 6

Institutions

3

  1. Stanford University

    Stanford, United States

    1 h-index

    3 publications

    168 citations

  2. Stanford Health Care

    Stanford, United States

    1 h-index

    1 publications

    56 citations

  3. Peking University

    Beijing, China

    1 h-index

    2 publications

    46 citations

1–3 of 3

Venues

  1. BMJ Quality & Safety

    1 publications · 56 citations

    1

    h-index

1–1