Content Change Detection

Content Change Detection is a systematic methodology in web forensics that identifies and analyzes alterations to web content over time by comparing historical and current states of digital artifacts to determine the nature, extent, and timing of modifications.

111

Publications

4.5K

Citations

301

Authors

107

Institutions

Publications per year

2017–2026

15

Authors

301

  1. SD
    Susan Dumais

    Microsoft (United States), United States

    5 publications · 364 citations

    5

    h-index

  2. RF
    Richard Furuta

    Texas A&M University, United States

    4 publications · 103 citations

    4

    h-index

  3. JT
    Jaime Teevan

    Microsoft (United States), United States

    4 publications · 273 citations

    4

    h-index

  4. UP
    Unmil P. Karadkar

    Texas A&M University, United States

    4 publications · 103 citations

    4

    h-index

  5. FS
    Frank Shipman

    Texas A&M University, United States

    4 publications · 103 citations

    4

    h-index

1–5 of 301

Venues

  1. Data & Knowledge Engineering

    DKE · 4 publications · 80 citations

    4

    h-index

  2. 2

    h-index

  3. IEEE Access

    2 publications · 106 citations

    2

    h-index

  4. ACM Transactions on Internet Technology

    TOIT · 2 publications · 365 citations

    2

    h-index

  5. Bioscience Biotechnology and Biochemistry

    1 publications · 18 citations

    1

    h-index

1–5