Automated Document Processing
Automated Document Processing is a systematic computational method that transforms unstructured or semi-structured document inputs into structured, analyzable data through the application of machine learning, natural language processing, and pattern recognition techniques, distinguishing it from manual or rule-based document handling by its adaptive, scalable, and intelligent processing capabilities.
394
Publications
18.6K
Citations
1.1K
Authors
420
Institutions
Publications per year
2017–2026
87
Parents
394
A Business Intelligence System
H. P. Luhn · IBM Journal of Research and Development · 1958 · 727 citations
Extracting structured data from Web pages
Arvind Arasu, Héctor García-Molina · 2003 · 701 citations
Web data extraction based on partial tree alignment
Yanhong Zhai, Bing Liu · 2005 · 495 citations
1–5 of 394
1.1K
10
h-index
8
h-index
8
h-index
7
h-index
German Research Centre for Artificial Intelligence, Germany
6 publications · 217 citations
6
h-index
1–5 of 1.1K
420

Concordia University
Montreal, Canada
11 h-index
31 publications
1.1K citations

Université de Rouen Normandie
Rouen, France
10 h-index
35 publications
959 citations
University of Bari Aldo Moro
Bari, Italy
10 h-index
42 publications
973 citations

Indian Statistical Institute
Kolkata, India
8 h-index
15 publications
551 citations
German Research Centre for Artificial Intelligence
Kaiserslautern, Germany
8 h-index
18 publications
516 citations
IBM (United States)
Armonk, United States
7 h-index
16 publications
1.2K citations
Laboratoire Lorrain de Recherche en Informatique et ses Applications
Nancy, France
6 h-index
9 publications
272 citations
University at Buffalo, State University of New York
Buffalo, United States
6 h-index
17 publications
525 citations
1–8 of 420
TPAMI · 7 publications · 625 citations
7
h-index
Repository · 7 publications · 156 citations
7
h-index
6 publications · 119 citations
6
h-index
5 publications · 467 citations
5
h-index
5 publications · 272 citations
5
h-index
1–5