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Machine Learning-Based System for Automated Presentation Generation from CSV Data

By
Rajkumar N ,
Rajkumar N

Alliance University

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Balusamy Nachiappan ,
Balusamy Nachiappan

Prologis, Denver, Colorado 80202 USA

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C. Kalpana ,
C. Kalpana

Computer Science and Engineering, Karpagam Institute of Technology, Coimbatore. India

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Mohanraj A ,
Mohanraj A

Department of Computer Science & Engineering, Sri Eshwar College of Engineering, Coimbatore, Tamil Nadu, India

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B Prabhu Shankar ,
B Prabhu Shankar

Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology, Chennai, Tamil Nadu, India

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C Viji ,
C Viji

Department of Computer Science & Engineering, Alliance College of Engineering and Design, Alliance University, Bangalore, Karnataka, India

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Abstract

Effective presentation slides are crucial for conveying information efficiently, yet existing tools lack content analysis capabilities. This paper introduces a content-based PowerPoint presentation generator, aiming to address this gap. By leveraging automated techniques, slides are generated from text documents, ensuring original concepts are effectively communicated. Unstructured data poses challenges for organizations, impacting productivity and profitability. While traditional methods fall short, AI-based approaches offer promise. This systematic literature review (SLR) explores AI methods for extracting Data from unstructured details. Findings reveal limitations in existing methods, particularly in handling complex document layouts. Moreover, publicly available datasets are task-specific and of low quality, highlighting the need for comprehensive datasets reflecting real-world scenarios[1]. The SLR underscores the potential of Artificial-based approaches for information extraction but emphasizes the challenges in processing diverse document layouts. Proposed is a framework for constructing high-quality datasets and advocating for closer collaboration between businesses and researchers to address unstructured data challenges effectively.

How to Cite

1.
N R, Nachiappan B, Kalpana C, Mohanraj A, Prabhu Shankar B, Viji C. Machine Learning-Based System for Automated Presentation Generation from CSV Data. Data and Metadata [Internet]. 2024 Jul. 2 [cited 2024 Jul. 15];3:359. Available from: https://dm.saludcyt.ar/index.php/dm/article/view/359

The article is distributed under the Creative Commons Attribution 4.0 License. Unless otherwise stated, associated published material is distributed under the same licence.

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