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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
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
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Issue: February 2026
Volume 11 | Issue 2
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 117
Article Submitted : 21303
Article Published : 8476
Total Authors : 22301
Total Reviewer : 802
Total Countries : 156
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Published Paper Details
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| Paper Title: | Ai-Powered Research Assistant for Information Analysis |
| Authors Name: | Yash Paithane , Suvarna D. Pingle |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_208341
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| Published Paper Id: | IJRTI2512042 |
| Published In: | Volume 10 Issue 12, December-2025 |
| DOI: | |
| Abstract: | Abstract— In the contemporary research landscape, the explosion of digital information has created both opportunities and challenges for scholars. The abundance of textual data across journals, online repositories, and reports has made manual analysis increasingly time-consuming and cognitively demanding. This paper presents an AI-Powered Research Assistant designed to automate key stages of the information analysis process through advanced Natural Language Processing (NLP) and Machine Learning (ML) methodologies. The proposed system integrates automated summarization, keyword extraction, frequency distribution analysis, and relational text mapping to assist individual researchers in efficiently organizing and interpreting vast academic datasets. Unlike large-scale enterprise analytics systems, this AI Research Assistant is developed as a personal intelligent companion, providing a tailored, interactive, and adaptive environment for research-oriented tasks. Built using Node.js, Express.js, PostgreSQL, and the OpenAI API, the system offers semantic understanding, efficient data retrieval, and dynamic keyword frequency evaluation. Results demonstrate that the proposed solution significantly reduces research time while improving the quality of information comprehension and organization. |
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| Cite Article: | "Ai-Powered Research Assistant for Information Analysis", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 12, page no.a345-a348, December-2025, Available :http://www.ijrti.org/papers/IJRTI2512042.pdf |
| Downloads: | 000173 |
| 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: IJRTI2512042
Registration ID:208341
Published In: Volume 10 Issue 12, December-2025
DOI (Digital Object Identifier):
Page No: a345-a348 Country: Chhatrapati Sambhajinagar, Maharashtra, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2512042 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2512042 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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