Iterative Data Processing

Iterative Data Processing is a distributed data processing paradigm that belongs to the class of data processing methods and is distinguished by its repeated execution of computational steps over the same dataset until a convergence criterion or termination condition is satisfied.

175

Publications

8.5K

Citations

530

Authors

248

Institutions

Publications per year

2017–2026

45

Authors

530

  1. CW
    Cuirong Wang

    Northeastern University, China

    5 publications · 523 citations

    5

    h-index

  2. YZ
    Yanfeng Zhang

    Northeastern University, China

    5 publications · 523 citations

    5

    h-index

  3. LG
    Lixin Gao

    University of Massachusetts Amherst, United States

    5 publications · 523 citations

    5

    h-index

  4. VM
    Volker Markl

    Technische Universität Berlin, Germany

    4 publications · 124 citations

    4

    h-index

  5. QG
    Qixin Gao

    Northeastern University, China

    4 publications · 462 citations

    4

    h-index

1–5 of 530

Venues

  1. Applied Mathematics and Computation

    6 publications · 131 citations

    6

    h-index

  2. 6

    h-index

  3. arXiv (Cornell University)

    Repository · 4 publications · 183 citations

    4

    h-index

  4. IEEE Transactions on Wireless Communications

    4 publications · 126 citations

    4

    h-index

  5. Proceedings of the VLDB Endowment

    PVLDB · 4 publications · 143 citations

    4

    h-index

1–5