Advanced Document Query System

Year : 2024 | Volume : 02 | Issue : 02 | Page : 26 35
    By

    Jyoti Jayesh Chavhan,

  • Shoaib Hafiz Shaikh,

  • Suyash Kiran Ayachit,

  • Sheshasai Arjun Dusa,

  • Nivedh Vijay Anakakkil,

  1. Assistant Professor, Department of Artificial Intelligence Machine Learning, SIES Graduate School of Technology, Nerul, Navi-Mumbai, Maharashtra, India
  2. Student, Department of Artificial Intelligence Machine Learning, SIES Graduate School of Technology, Nerul, Navi-Mumbai, Maharashtra, India
  3. Student, Department of Artificial Intelligence Machine Learning, SIES Graduate School of Technology, Nerul, Navi-Mumbai, Maharashtra, India
  4. Student, Department of Artificial Intelligence Machine Learning, SIES Graduate School of Technology, Nerul, Navi-Mumbai, Maharashtra, India
  5. Student, Department of Artificial Intelligence Machine Learning, SIES Graduate School of Technology, Nerul, Navi-Mumbai, Maharashtra, India

Abstract

For knowledge-intensive businesses, large document libraries contain a plethora of information. Massive, chaotic, collections of documents that are unstructured have emerged from this rapid increase. Even if accessing or storing these documents has become easier, finding the required critical information in these vast document collections has become more difficult. NLP (natural language processing) is one of the techniques used to retrieve the information that is required from a huge chunk of data. The proposed system uses cutting-edge methods for document comprehension and NLP to enable users to upload PDFs, ask questions, and get timely, accurate answers. NLP techniques use the subtle layers of context and semantics, going beyond simple keyword extraction. The interface facilitates easy interaction with complex textual material by providing users with access to a multitude of information. Regardless of your experience level, level of diligence, or role as a multi-disciplinary expert, the platform meets a wide range of needs and fluidly adjusts to meet each user’s specific needs. This initiative stands out as a pathfinder as we traverse the digital world, where information is plentiful but frequently difficult to extract. It not only makes it easier to interact with textual content, but it also creates an ecosystem where insights are easily available to everyone. It is evidence of how innovation can create a knowledge environment that is inclusive of all people and productive, paving the way for a genuinely inclusive digital age.

Keywords: NLP, user-friendly, innovation, information retrieval, extraction

[This article belongs to International Journal of Computer Science Languages ]

How to cite this article:
Jyoti Jayesh Chavhan, Shoaib Hafiz Shaikh, Suyash Kiran Ayachit, Sheshasai Arjun Dusa, Nivedh Vijay Anakakkil. Advanced Document Query System. International Journal of Computer Science Languages. 2024; 02(02):26-35.
How to cite this URL:
Jyoti Jayesh Chavhan, Shoaib Hafiz Shaikh, Suyash Kiran Ayachit, Sheshasai Arjun Dusa, Nivedh Vijay Anakakkil. Advanced Document Query System. International Journal of Computer Science Languages. 2024; 02(02):26-35. Available from: https://journals.stmjournals.com/ijcsl/article=2024/view=177659


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Regular Issue Subscription Review Article
Volume 02
Issue 02
Received 27/06/2024
Accepted 08/09/2024
Published 07/10/2024
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