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Deep Understanding of Technical Documents: An Enhancement on Diagrams Understanding.

Authors :
Alexiou, Michail S.
Gkorgkolis, Nikolaos
Mertoguno, Sukarno
Bourbakis, Nikolaos G.
Source :
International Journal on Artificial Intelligence Tools. Aug2021, Vol. 30 Issue 5, p1-21. 21p.
Publication Year :
2021

Abstract

Humans are capable of understanding the knowledge that is included in technical documents automatically by consciously combining the information that is presented in the document's individual modalities. These modalities are mathematical formulas, charts, tables, diagram images and etc. In this paper, we significantly enhance a previously presented technical document understanding methodology3 that emulates the way that humans also perceive information. More specifically, we make the original diagram understanding methodology adaptive to larger architectures with more complex structures and modules. The overall understanding methodology results in the generation of a Stochastic Petri-net (SPN) graph that describes the system's functionality. Finally, we conclude with the introduction of the hierarchical association of different diagram images from the same technical document. This processing step aims to provide a holistic understanding of all illustrated diagram information. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02182130
Volume :
30
Issue :
5
Database :
Academic Search Index
Journal :
International Journal on Artificial Intelligence Tools
Publication Type :
Academic Journal
Accession number :
152185322
Full Text :
https://doi.org/10.1142/S0218213021500275