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IoT 24(1):

Editorial

Cloud Based Document Understanding System

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  • @ARTICLE{10.4108/eetiot.5390,
        author={Parth Rewoo and Aditya Kumar Jaiswal and Durvesh Mahajan and Harshit Naidu},
        title={Cloud Based Document Understanding System},
        journal={EAI Endorsed Transactions on Internet of Things},
        volume={10},
        number={1},
        publisher={EAI},
        journal_a={IOT},
        year={2024},
        month={3},
        keywords={Cloud-based system, Document understanding, Natural language processing, Optical character recognition, OCR, Text extraction, Scalability},
        doi={10.4108/eetiot.5390}
    }
    
  • Parth Rewoo
    Aditya Kumar Jaiswal
    Durvesh Mahajan
    Harshit Naidu
    Year: 2024
    Cloud Based Document Understanding System
    IOT
    EAI
    DOI: 10.4108/eetiot.5390
Parth Rewoo1,*, Aditya Kumar Jaiswal1, Durvesh Mahajan1, Harshit Naidu1
  • 1: AISSMS Institute of Information Technology
*Contact email: rewooparth.rp@gmail.com

Abstract

In recent years, the popularity of cloud-based systems has been on the rise, particularly in the field of document management. One of the main challenges in this area is the need for effective document understanding, which involves the extraction of meaningful information from unstructured data. To address this challenge, we propose a cloud-based document understanding system that leverages state-of-the-art machine learning techniques and natural language processing algorithms. This system utilizes a combination of optical character recognition (OCR), text extraction, and machine learning models to extract and classify relevant information from documents. The system is designed to be scalable and flexible, allowing it to handle large volumes of data and adapt to different document types and formats. Additionally, our system employs advanced security measures to ensure the confidentiality and integrity of the processed data. This cloud-based document understanding system has the potential to significantly improve document management processes in various industries, including healthcare, legal, and finance.

Keywords
Cloud-based system, Document understanding, Natural language processing, Optical character recognition, OCR, Text extraction, Scalability
Received
2023-12-12
Accepted
2024-03-07
Published
2024-03-12
Publisher
EAI
http://dx.doi.org/10.4108/eetiot.5390

Copyright © 2024 P. Rewoo et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

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