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Computer Science > Computation and Language

arXiv:2109.11603 (cs)
[Submitted on 23 Sep 2021]

Title:Document Automation Architectures and Technologies: A Survey

Authors:Mohammad Ahmadi Achachlouei, Omkar Patil, Tarun Joshi, Vijayan N. Nair
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Abstract:This paper surveys the current state of the art in document automation (DA). The objective of DA is to reduce the manual effort during the generation of documents by automatically integrating input from different sources and assembling documents conforming to defined templates. There have been reviews of commercial solutions of DA, particularly in the legal domain, but to date there has been no comprehensive review of the academic research on DA architectures and technologies. The current survey of DA reviews the academic literature and provides a clearer definition and characterization of DA and its features, identifies state-of-the-art DA architectures and technologies in academic research, and provides ideas that can lead to new research opportunities within the DA field in light of recent advances in artificial intelligence and deep neural networks.
Comments: 34 pages, 11 figures, 5 tables
Subjects: Computation and Language (cs.CL); Machine Learning (cs.LG)
MSC classes: 68T50
ACM classes: I.7.0; I.2.7; I.2.4
Cite as: arXiv:2109.11603 [cs.CL]
  (or arXiv:2109.11603v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2109.11603

Submission history

From: Mo Achachlouei [view email]
[v1] Thu, 23 Sep 2021 19:12:26 UTC (1,369 KB)
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