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Intelligent Document Processing in End-to-End RPA Contexts: A Systematic Literature Review

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Confluence of Artificial Intelligence and Robotic Process Automation

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 335))

Abstract

Automating organizational processes typically involves document processing techniques for a large document set. For that purpose, the Intelligent Document Processing (IDP) paradigm has been studied for decades. With the fast emergence of Robotic Process Automation (RPA) in the process automation landscape, the industrial solution of IDP with RPA integration has risen significantly in the last few years. However, there is no up-to-date overview of the available knowledge in this area. Therefore, this chapter studies the current scientific knowledge about IDP and its integration into RPA through a systematic literature review that analyzed 77 primary studies. In addition, an industry review was performed, analyzing and characterizing 37 industrial tools. Although the results confirm the growth in the research interest in IDP in different dimensions, they also identify a lack of proposals that integrate IDP and RPA paradigms in confrontation with the industrial solutions that have increasingly led to its integration.

This research has been supported by the NICO project (PID2019-105455GB-C31) of the Spanish Ministry of Science, Innovation and Universities and the CODICE project (EXP 00130458/IDI-20210319 - P018-20/E09) of the Center for the Development of Industrial Technology (CDTI) and by the FPU scholarship program, granted by the Spanish Ministry of Education and Vocational Training (FPU20/05984).

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Notes

  1. 1.

    https://www.automationanywhere.com/rpa/intelligent-document-processing.

  2. 2.

    https://www.abbyy.com/flexicapture/.

  3. 3.

    A complete analysis of the analysis executed can be found on the sheet with the title “Scientific” within the Excel document available at https://doi.org/10.5281/zenodo.6400519.

  4. 4.

    https://www.google.es/.

  5. 5.

    https://www.bing.com.

  6. 6.

    https://search.aol.com/aol/webhome.

  7. 7.

    The relationship between these tools and the characteristics described in Table 5.11 are shown in the sheet with the title “Industrial” in the Excel document available at https://doi.org/10.5281/zenodo.6400519.

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  1. Departamento de Lenguajes y Sistemas Informáticos, Escuela Técnica Superior de Ingeniería Informática, Avenida Reina Mercedes, s/n., 41012, Sevilla, Spain

    A. Martínez-Rojas, J. M. López-Carnicer, J. González-Enríquez & A. Jiménez-Ramírez

  2. Servinform, S.A. Parque Industrial PISA, Calle Manufactura, 5, 41927, Mairena del Aljarafe, Sevilla, Spain

    J. M. Sánchez-Oliva

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  1. A. Martínez-Rojas
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  1. Algebra University College, Zagreb, Croatia

    Siddhartha Bhattacharyya

  2. Department of Computer Science and Engineering (AI & ML), Bengal Institute of Technology, Kolkata, India

    Jyoti Sekhar Banerjee

  3. Department of Computer Science and Engineering, Maulana Abul Kalam Azad University of Technology, Kolkata, West Bengal, India

    Debashis De

Appendix A: List of Abbreviations

Appendix A: List of Abbreviations

 

RPA:

      Robotic Process Automation

IDP:

      Intelligent Document Processing

AI:

      Artificial Intelligence

OCR:

      Optical Character Recognition

SLR:

      Systematic Literature Review

RQs:

      Research Questions

 

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Martínez-Rojas, A., López-Carnicer, J.M., González-Enríquez, J., Jiménez-Ramírez, A., Sánchez-Oliva, J.M. (2023). Intelligent Document Processing in End-to-End RPA Contexts: A Systematic Literature Review. In: Bhattacharyya, S., Banerjee, J.S., De, D. (eds) Confluence of Artificial Intelligence and Robotic Process Automation. Smart Innovation, Systems and Technologies, vol 335. Springer, Singapore. https://doi.org/10.1007/978-981-19-8296-5_5

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