A Holistic Approach for Automatic Deep Understanding and Protection of Technical Documents

Author:

Bourbakis Nikolaos1,Mertoguno Sukarno2

Affiliation:

1. CART, Wright State University, Dayton, OH, United States

2. Georgia Tech, GTRI, GA, United States

Abstract

A Technical Document (TD) is mainly composed by a set of modalities appropriately structured and associated. These modalities could be NL-text, block diagrams, formulas, tables, graphics, pictures etc. A deep understanding of a TD will be based on the synergistic understanding and associations of these modalities. This paper offers a novel methodology for the implementation of a holistic approach for deep understanding of technical documents by understanding and associating these modalities. This approach is based on the homogeneous expression (mapping) of the technical document modalities into the same medium, which in this case is the Stochastic Petri-nets (SPN). Then, these modalities are associated to each other generating new knowledge about the technical document topic and a SPN simulator is created to offer additional information about the functional behavior of the system described in the document. Some results from our studies are provided to prove the overall concept.

Publisher

World Scientific Pub Co Pte Lt

Subject

Artificial Intelligence,Artificial Intelligence

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Extracting Pseudocode from Digital Block Diagram in Technical Documents;International Journal on Artificial Intelligence Tools;2023-09

2. Key–Value Pair Identification from Tables Using Multimodal Learning;International Journal of Pattern Recognition and Artificial Intelligence;2023-04-29

3. Intelligent Document Processing in End-to-End RPA Contexts: A Systematic Literature Review;Confluence of Artificial Intelligence and Robotic Process Automation;2023

4. Detection, Extraction and SPN Representation of Pseudo-Algorithms in Scientific Documents;Handbook on Artificial Intelligence-Empowered Applied Software Engineering;2022

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3