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Contextual video analytics and recommendations through natural language processing (NLP) and graph machine learning (GML)

Authors

  • Umm-e-Laila

    College of Computer Science & Information Systems, Institute of Business Management, Karachi, Pakistan
    Author

  • Khalid Mahboob

    College of Computer Science & Information Systems, Institute of Business Management, Karachi, Pakistan
    Author

  • Muzammil Ahmed Khan

    Computer Engineering Department, Sir Syed University of Engineering and Technology, Karachi, Pakistan
    Author

  • Muhammad Khurram

    University of Technology and Applied Sciences, Nizwa, Sultanate of Oman
    Author

  • Mustafa Ahmed Khan

    College of Computer Science & Information Systems, Institute of Business Management, Karachi, Pakistan
    Author
    https://orcid.org/0009-0008-5656-9163

DOI:

https://doi.org/10.22581/muet1982.0220

Keywords:

Natural Language Processing (NLP) , Sentiment Analysis , Graph ML , Content Analysis, Keyword Extraction

Abstract

This research paper explores an innovative approach to video recommender systems by integrating Natural Language Processing (NLP) techniques, graph databases, and advanced analytics. The smart content recommender system goes beyond traditional title or description-based recommendations, aiming to enhance user experience through content-level searching capabilities and spoken-word analysis within videos. Through sentiment analysis (SA), topic analysis (TA), and keyword extraction (KWE), the system tags and timestamps the video transcripts in a detailed and contextual manner and offers recommendations. Since the study is underpinned by Graph Machine Learning (GML) literature, it is informed by a call for recognizing keywords spoken in videos more efficiently. It responds to questions about recommending content with less explicit information and adds new solutions like voice search and multi-language interface to improve accessibility. This idea may appeal to industries that want to receive videos from the targeted population with state-of-the-art content analysis.

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References

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Published

2025-07-01

Issue

Vol. 44 No. 3 (2025): July Issue

Section

Articles

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Copyright (c) 2025 Mehran University Research Journal of Engineering and Technology

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite

Contextual video analytics and recommendations through natural language processing (NLP) and graph machine learning (GML). (2025). Mehran University Research Journal of Engineering and Technology, 44(3), 65-73. https://doi.org/10.22581/muet1982.0220

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