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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: May 2026
Volume 11 | Issue 5
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 120
Article Submitted : 24205
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Total Authors : 24597
Total Reviewer : 847
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| Paper Title: | Development of a RAG-Powered Chatbot for Government Services, answering citizen queries by retrieving from official government websites. |
| Authors Name: | R. Prabu Arokiyaraj , K. Saranya , S. Jesintha Chandrajothi , S. Latchya , J.Yogeswari |
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IJRTI_212207
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| Published Paper Id: | IJRTI2604341 |
| Published In: | Volume 11 Issue 4, April-2026 |
| DOI: | |
| Abstract: | This study aims to enhance the accessibility and precision of government service information by developing an intelligent chatbot system. Conventional approaches, including keyword-based search engines and rule-driven chatbots, frequently struggle to deliver accurate and contextually meaningful responses, which can result in user confusion and the spread of incorrect information. With the rapid growth of digital government data, manually locating relevant information has become increasingly inefficient for citizens. To address these challenges, the proposed system utilizes a Retrieval-Augmented Generation (RAG) framework. It gathers data from authorized government portals and official documents, processes the content using semantic analysis, and transforms it into vector embeddings stored within a vector database for fast and relevant retrieval. When a user submits a query, the system performs a semantic search to identify the most appropriate information and generates a response using a Large Language Model. By anchoring responses in verified and reliable sources, the chatbot minimizes misinformation and enhances trustworthiness. Additionally, a user-friendly web interface allows citizens to conveniently access information related to government schemes, eligibility requirements, and application processes. Experimental results indicate that the system significantly improves response accuracy, relevance, and overall user experience in accessing public service information. |
| Keywords: | Retrieval-Augmented Generation (RAG), Government Chatbot, Natural Language Processing (NLP), Large Language Models (LLM), Semantic Search, Vector Database. |
| Cite Article: | "Development of a RAG-Powered Chatbot for Government Services, answering citizen queries by retrieving from official government websites.", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.c568-c573, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604341.pdf |
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| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2604341
Registration ID:212207
Published In: Volume 11 Issue 4, April-2026
DOI (Digital Object Identifier):
Page No: c568-c573 Country: Tiruvannamalai, Tamilnadu, India Research Area: Information Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2604341 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2604341 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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