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ESTD2016
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Paper Title
Embedding-Based Vector Search for Large Scale Text Retrieval
Authors
Dr Vinod Kumar P , Kampana R , Neha Merin D`Souza , Nishanth M Jadav , Sharath P
Keywords
Vector Search ,Semantic Similarity, Embedding Generation ,Natural Language Processing (NLP) ,FAISS ,Retrieval-Augmented Generation (RAG) , Generative Al , Information Retrieval
Abstract
Embedding-based vector search marks a
transformative shift in information Re-trieval,
particularly for large-scale textual datasets where
conventional keyword-based methods fall short in
capturing semantic relevance. This approach reframes
text retrieval as a semantic similarity task, representing
documents—such as legal or academic texts—as high-
dimensional vector embeddings using advanced natural
language processing (NLP) models like BERT or
RoBERTa. These embeddings encapsulate the
contextual and conceptual essence of the documents,
enabling re-trieval based on meaning rather than exact
keyword matches.
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IJRTI — journal style
"Embedding-Based Vector Search for Large Scale Text Retrieval", IJRTI - International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.10, Issue 8, page no.b448-b450, August-2025, Available :https://ijrti.org/papers/IJRTI2508158.pdf
APA — 7th edition
P, V. K., R, K., D`Souza, N. M., Jadav, N. M., & P, S. (2025). Embedding-Based Vector Search for Large Scale Text Retrieval. International Journal for Research Trends and Innovation, 10(8), b448-b450. https://ijrti.org/viewpaperforall.php?paper=IJRTI2508158
MLA — 9th edition
P, Vinod Kumar, et al. "Embedding-Based Vector Search for Large Scale Text Retrieval." International Journal for Research Trends and Innovation, vol. 10, no. 8, 2025, pp. b448-b450, https://ijrti.org/viewpaperforall.php?paper=IJRTI2508158.
Chicago — 17th, bibliography
P, Vinod Kumar, et al. "Embedding-Based Vector Search for Large Scale Text Retrieval." International Journal for Research Trends and Innovation 10, no. 8 (2025): b448-b450. https://ijrti.org/viewpaperforall.php?paper=IJRTI2508158.
Harvard — author–date
P, V.K. et al. (2025) 'Embedding-Based Vector Search for Large Scale Text Retrieval', International Journal for Research Trends and Innovation, 10(8), pp. b448-b450. Available at: https://ijrti.org/viewpaperforall.php?paper=IJRTI2508158
IEEE — numbered reference
V. K. P, K. R, N. M. D`Souza, N. M. Jadav and S. P, "Embedding-Based Vector Search for Large Scale Text Retrieval," IJRTI, vol. 10, no. 8, pp. b448-b450, Aug. 2025.
Vancouver — biomedical
P VK, R K, D`Souza NM, Jadav NM, P S. Embedding-Based Vector Search for Large Scale Text Retrieval. IJRTI. 2025 Aug;10(8):b448-b450.
AMA — 11th edition
P VK, R K, D`Souza NM, Jadav NM, P S. Embedding-Based Vector Search for Large Scale Text Retrieval. IJRTI. 2025;10(8):b448-b450. Accessed at https://ijrti.org/viewpaperforall.php?paper=IJRTI2508158
BibTeX — Zotero, Mendeley, LaTeX
@article{IJRTI2508158,
author = {Vinod Kumar P and Kampana R and Neha Merin D`Souza and Nishanth M Jadav and Sharath P},
title = {Embedding-Based Vector Search for Large Scale Text Retrieval},
journal = {International Journal for Research Trends and Innovation},
volume = {10},
number = {8},
pages = {b448-b450},
year = {2025},
month = {August},
issn = {2456-3315},
url = {https://ijrti.org/viewpaperforall.php?paper=IJRTI2508158}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - P, Vinod Kumar
AU - R, Kampana
AU - D`Souza, Neha Merin
AU - Jadav, Nishanth M
AU - P, Sharath
TI - Embedding-Based Vector Search for Large Scale Text Retrieval
T2 - International Journal for Research Trends and Innovation
JA - IJRTI
VL - 10
IS - 8
PY - 2025
SN - 2456-3315
UR - https://ijrti.org/viewpaperforall.php?paper=IJRTI2508158
SP - b448-b450
ER -
Issue
Volume 10 Issue 8,
August-2025
Pages : b448-b450
Other Publication Details
Paper Reg. ID
IJRTI_205887
Published Paper ID
IJRTI2508158
Downloads
205,643
Research Area
Engineering
Country
Mysuru, Karnataka, India
Published
August 2025
Published Paper PDF
https://ijrti.org/papers/IJRTI2508158.pdf
Published Paper URL
https://ijrti.org/viewpaperforall.php?paper=IJRTI2508158
About Publisher
International Journal for Research Trends and Innovation
Published by IJRTI (JW Publication)
2456-3315
ISSN
10.57
Impact Factor
2016
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Open
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Impact Factor 10.57 calculated by Google Scholar and Semantic Scholar.
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Declarations
Funding
No external funding was received for this study.
Conflict of Interest
The authors declare that they have no conflict of interest.
Acknowledgements
The authors would like to thank the reviewers and the editorial board of International Journal for Research Trends and Innovation for their careful reading and constructive comments, and all colleagues who supported the preparation of this manuscript.
