Graph Based Abstractive Text Summarization of YouTube Comments
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Research Paper | Computer Engineering | India | Volume 12 Issue 6, June 2023 | Popularity: 5.2 / 10


     

Graph Based Abstractive Text Summarization of YouTube Comments

Vijayendra S. Gaikwad


Abstract: Summarizing documents or reviews has received a lot of attention in recent years due to the explosive expansion of online documents having large sizes and shopping websites having a large number of reviews. In this fast-paced environment, people require things to be done fast, saving time. Reviews and documents are being created in enormous quantities every day. Understanding the context of document/ reviews and converting them into a specific format, like a summary to conserve storage space and aid in information acquisition in a short period of time. We test a hybrid end-to-end model solution that synthesizes input video comments and abstract text summaries using natural language processing and graph-based methods. This methodology first provides an extractive text summary of the comments. We propose a joint end-to-end model using the FP-Growth method and T5 Model for generating an abstractive text summary of the video input provided.


Keywords: Machine learning, Deep learning, Natural Language Processing, Extractive & Abstractive Summary


Edition: Volume 12 Issue 6, June 2023


Pages: 913 - 918


DOI: https://www.doi.org/10.21275/SR23604110517


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Vijayendra S. Gaikwad, "Graph Based Abstractive Text Summarization of YouTube Comments", International Journal of Science and Research (IJSR), Volume 12 Issue 6, June 2023, pp. 913-918, https://www.ijsr.net/getabstract.php?paperid=SR23604110517, DOI: https://www.doi.org/10.21275/SR23604110517

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