Concepedia

Entropy-based Carving

Entropy-Based Carving is a data carving method that identifies and extracts structured data units from unstructured or semi-structured sources by leveraging information entropy to distinguish regions of high randomness (non-data) from low entropy (potential data segments).

2

Publications

24

Citations

8

Authors

6

Institutions

Publications per year

2017–2026

1

Parents

Publications

2

1–2 of 2

Authors

8

  1. HT
    Hüsrev Taha Sencar

    New York University, United States

    1 publications · 13 citations

    1

    h-index

  2. EU
    Erkam Uzun

    TOBB University of Economics and Technology, Türkiye

    1 publications · 13 citations

    1

    h-index

  3. WQ
    Weidong Qiu

    Shanghai Jiao Tong University, China

    1 publications · 11 citations

    1

    h-index

  4. BL
    Bozhong Liu

    Shanghai Jiao Tong University, China

    1 publications · 11 citations

    1

    h-index

  5. ZH
    Zheng Huang

    University of Colorado Denver, United States

    1 publications · 11 citations

    1

    h-index

1–5 of 8

Institutions

6

  1. Georgia Institute of Technology

    Atlanta, United States

    1 h-index

    1 publications

    13 citations

  2. Qatar Airways (Qatar)

    Doha, Qatar

    1 h-index

    1 publications

    13 citations

  3. China Construction Bank

    Beijing, China

    1 h-index

    1 publications

    11 citations

  4. Bank of China

    Beijing, China

    1 h-index

    1 publications

    11 citations

  5. Shanghai Jiao Tong University

    Shanghai, China

    1 h-index

    5 publications

    55 citations

  6. TOBB University of Economics and Technology

    Ankara, Türkiye

    1 h-index

    1 publications

    13 citations

1–6 of 6

Venues

  1. 1

    h-index

1–1