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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM65308
Volume:
10 |
6 |
Jun 2026
Pages:
1-8
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Computer Engineering
Sinhgad Academy of Engineering,pune.
Department of Computer Engineering
Sinhgad Academy of Engineering,pune.
Department of Computer Engineering
Sinhgad Academy of Engineering,pune.
Department of Computer Engineering
Sinhgad Academy of Engineering,pune.
The exponential growth of digital data has significantly increased the demand for intelligent systems that simplify document comprehension and accelerate information retrieval. Manual reading and analysis of lengthy documents remain cognitively demanding and time-consuming, particularly in academia, research, and professional environments. This review paper examines existing artificial intelligence-based solutions in document processing, including text summarization, natural language querying, annotation systems, and knowledge visualization techniques. It highlights how these technologies aim to improve efficiency but still face limitations in usability, integration, and user interaction. Based on the gaps identified in current systems, this paper introduces ChatMyDoc, a natural language-driven document interaction assistant designed to enhance user understanding and productivity. Built using modern web technologies and advanced AI models, the system supports PDF querying, abstractive and extractive summarization, annotation storage, and automated flowchart generation. The design focuses on reducing cognitive load, improving accessibility, and enabling intuitive interaction with digital content.
KEYWORDS
This paper presented ChatMyDoc, an intelligent document interaction system designed to simplify document understanding and improve information retrieval. By integrating features such as PDF querying, summarization, annotation, and flowchart generation, the system provides a unified and efficient platform for users to interact with digital documents. The use of modern technologies like the MERN stack and AI-based processing enhances performance and usability. Overall, ChatMyDoc effectively reduces cognitive effort and offers a practical solution for academic, research, and professional applications.
-Based Feature Extraction Technique for Single Document IEEE Access, vol. 13, pp. 24515–24521, Feb. 2025. S. A. Azam et al., “Current Comprehensive Review,” K. Papineni et al., “BLEU: A Method for Automatic Evaluation of Machine Translation,” in Proc. ACL, pp. 311–318, 2002. Trends and Advances in Extractive Text Summarization: A IEEE Access, vol. 12, pp. 114586–114612, 2024. C. Lin, “ROUGE: A Package for Automatic Evaluation of Summaries,” in Proc. ACL Workshop, pp. 74–81, 2004. Found. Trends Inf. Retrieval, vol. 5, no. 2–3, pp. 103–233, 2012. “Distributed Representations of Words and Phrases and their” Proc. NeurIPS, 2013.
Publication Date
6/22/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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