Document Cognition - Information Search and Retrieval in Chatbots

Registration ID: IJNRD_198310

Published ID: IJNRD2306099

DOI: Click Here to Get

P. V. Koundinya

In today's digital age, the abundance of information poses a significant challenge in efficiently accessing and retrieving relevant documents, which has led to a growing market demand for advanced document information search and retrieval systems. This project aims to address this market need by developing a robust and accurate system, using various machine learning techniques and natural language processing algorithms, that enables users to quickly find and retrieve pertinent information from large document repositories. The methodology employed in this project involves evaluating and benchmarking various document information search and retrieval models. The project starts with extensive data preprocessing to ensure data quality and consistency. Next, a range of models, including Deeplake and ChromaDB, are trained using state-of-the-art techniques. The trained models are then rigorously evaluated based on their performance metrics, including accuracy and retrieval time, to determine their effectiveness in real-world scenarios.  The quantitative results obtained from the evaluation phase demonstrate the capabilities of the models in terms of accuracy and efficiency. Deeplake achieved an impressive accuracy of 90.25% with an average retrieval time of 0.6 seconds, while ChromaDB demonstrated a remarkable accuracy of 91.4% with an average retrieval time of 0.8 seconds. These results highlight the potential of these models to deliver accurate and timely search results, providing significant value to users in terms of time savings and enhanced information retrieval capabilities.

Published Paper   E-Certificate

P. V. Koundinya (June-2023). Document Cognition - Information Search and Retrieval in Chatbots. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(6), a862-a866. https://ijnrd.org/papers/IJNRD2306099.pdf

Volume 8 Issue 6, June-2023

Pages : a862-a866

Paper Reg. ID: IJNRD_198310

Published Paper Id: IJNRD2306099

Downloads: 000121153

Research Area: Computer Science & Technology 

Country: Bangalore, Karnataka, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2306099.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2306099

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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Call For Paper - Volume 10 | Issue 9 | September 2025

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