Paper Title :Harnessing Large Language Models for Document Querying
Author :G.h. Wani, Ayush Chiddarwar, Saif Bagmaru, Aditya Bhad, Farhan Attar
Article Citation :G.h. Wani ,Ayush Chiddarwar ,Saif Bagmaru ,Aditya Bhad ,Farhan Attar ,
(2024 ) " Harnessing Large Language Models for Document Querying " ,
International Journal of Advance Computational Engineering and Networking (IJACEN) ,
pp. 111-114,
Volume-12,Issue-7
Abstract : In the age of the information society, one of the most significant issues is being able to process and retrieve data
from different sources efficiently,thus producing actionable insights. In this work, we put forward a novel approximation of
the conventional technology through the joint use of advanced PDF mechanisms, text processing, and generative models.
The major innovation is due to the hidden topic modeling using Latent Dirichlet Allocation (LDA), where documents
become the source of their important keywords. These keywords are finally then sentence into the text generated by the
Large Language Models (LLM), improving the understanding of contexts and maximizing the accuracy of information
retrieval. The documentary outcomes represent the superiority of this approach being integrated which is shown by the
effectiveness of streamlining systems of document processing. This research study opens up a new frontier in information
retrieval by presenting the interactional structure between topic modeling and language model in document analysis.
Keywords - Document processing, Information retrieval, Text processing, Generative models, Latent Dirichlet
Allocation(LDA),Large Language Models (LLM), Topic modeling, Contextual understanding, Keyword extraction,
Information extraction, Document analysis.
Type : Research paper
Published : Volume-12,Issue-7
DOIONLINE NO - IJACEN-IRAJ-DOIONLINE-21106
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Copyright: © Institute of Research and Journals
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Published on 2024-10-17 |
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