Streaming Graph Algorithms

Streaming Graph Algorithms is a class of graph algorithms designed to process massive graphs in a streaming model, where edges or vertices arrive sequentially over time and the algorithm must make decisions with limited memory and a small number of passes over the data.

235

Publications

13.3K

Citations

497

Authors

197

Institutions

Publications per year

2017–2026

93

Authors

497

  1. AM
    Andrew McGregor

    University of Massachusetts Amherst, United States

    13 publications · 1.3K citations

    13

    h-index

  2. GC
    Graham Cormode

    AT&T (United States), United States

    12 publications · 264 citations

    10

    h-index

  3. SA
    Sepehr Assadi

    University of Pennsylvania, United States

    9 publications · 246 citations

    9

    h-index

  4. MK
    Michael Kapralov

    Stanford University, United States

    9 publications · 363 citations

    9

    h-index

  5. MM
    Morteza Monemizadeh

    University of Warwick, United Kingdom

    9 publications · 182 citations

    9

    h-index

1–5 of 497

Venues

  1. Proceedings of the VLDB Endowment

    PVLDB · 15 publications · 1.5K citations

    15

    h-index

  2. arXiv (Cornell University)

    Repository · 17 publications · 382 citations

    12

    h-index

  3. ACM Transactions on Knowledge Discovery from Data

    TKDD · 9 publications · 642 citations

    9

    h-index

  4. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)

    Repository · 9 publications · 217 citations

    9

    h-index

  5. Algorithmica

    7 publications · 210 citations

    7

    h-index

1–5