Unstructured Data Extraction

Unstructured Data Extraction is a data processing methodology that specifically enables the identification, parsing, and transformation of heterogeneous, non-tabular information—such as text, images, or audio—into structured formats suitable for computational analysis, distinguishing it from methods designed for structured or semi-structured data sources.

932

Publications

44.7K

Citations

3.4K

Authors

1.2K

Institutions

Publications per year

2017–2026

583

Authors

3.4K

  1. AD
    AnHai Doan

    University of Wisconsin–Madison, United States

    7 publications · 386 citations

    7

    h-index

  2. DW
    David W. Embley

    Brigham Young University, United States

    5 publications · 553 citations

    5

    h-index

  3. RR
    Raghu Ramakrishnan

    University of Wisconsin–Madison, United States

    5 publications · 279 citations

    5

    h-index

  4. RD
    Ralph Deters

    University of Saskatchewan, Canada

    5 publications · 111 citations

    5

    h-index

  5. RK
    Richard K. Lomotey

    University of Saskatchewan, Canada

    5 publications · 111 citations

    5

    h-index

1–5 of 3.4K

Venues

  1. BMC Medical Informatics and Decision Making

    19 publications · 672 citations

    15

    h-index

  2. arXiv (Cornell University)

    Repository · 14 publications · 331 citations

    13

    h-index

  3. PubMed

    Repository · 16 publications · 411 citations

    12

    h-index

  4. Procedia Computer Science

    9 publications · 489 citations

    10

    h-index

  5. Applied Sciences

    9 publications · 281 citations

    9

    h-index

1–5