Temporal Rule Mining

Temporal Rule Mining is a data mining technique that discovers temporal associations and recurring patterns in time-stamped data by identifying rules that characterize the sequential or timed relationships among events, thereby distinguishing itself from atemporal rule mining methods through its explicit incorporation of time constraints and temporal ordering.

69

Publications

3.4K

Citations

224

Authors

110

Institutions

Publications per year

2017–2026

11

Authors

224

  1. LS
    Lucia Sacchi

    University of Pavia, Italy

    4 publications · 215 citations

    4

    h-index

  2. RB
    Riccardo Bellazzi

    University of Pavia, Italy

    4 publications · 215 citations

    4

    h-index

  3. MC
    Ming-Syan Chen⋆

    National Taiwan University, Taiwan

    3 publications · 212 citations

    3

    h-index

  4. DL
    David Lo

    Singapore Management University, Singapore

    3 publications · 93 citations

    3

    h-index

  5. SJ
    Sushil Jajodia

    George Mason University, United States

    2 publications · 307 citations

    2

    h-index

1–5 of 224

Venues

  1. Applied Soft Computing

    2 publications · 85 citations

    2

    h-index

  2. PubMed

    Repository · 2 publications · 28 citations

    2

    h-index

  3. Proceedings of the VLDB Endowment

    PVLDB · 2 publications · 70 citations

    2

    h-index

  4. Knowledge-Based Systems

    2 publications · 56 citations

    2

    h-index

  5. Data & Knowledge Engineering

    DKE · 2 publications · 277 citations

    2

    h-index

1–5