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@article{187149,
        author = {MD MOHIUDDIN ANSARI and PIYUSH KUMAR SINGH and ASHISH RANJAN and REKHA B K},
        title = {YouTube Notes RAG-System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {4829-4833},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=187149},
        abstract = {With the massive surge in online educational and informational videos, users often struggle to extract precise knowledge from long-form content. This work introduces the YouTube Notes RAG-System — an intelligent, web-based framework designed to automatically obtain transcripts from YouTube videos, summarize them concisely using advanced Natural Language Processing (NLP) models, and provide an interactive question-answer feature. The system leverages transformer-based architectures such as T5, BART, and GPT to generate abstractive summaries and context-aware responses. By automating comprehension and facilitating conversational interaction with video content, the proposed model enhances accessibility, promotes active learning, and significantly reduces time spent on video navigation.},
        keywords = {},
        month = {November},
        }