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In today’s world, a large number of videos are uploaded in everyday, which contains information about something. The major challenge is to find the right video and understand the correct content, because there are lot of videos available some videos will contain useless content and even though the p...

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Bibliographic Details
Published in:E3S web of conferences 2023-01, Vol.399, p.4015
Main Authors: P, Ilampiray, D, Naveen Raju, A, Thilagavathy, M, Mohamed Tharik, S, Madhan Kishore, A.S, Nithin, I, Infant Raj
Format: Article
Language:English
Subjects:
Information processing
Video data
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Summary:In today’s world, a large number of videos are uploaded in everyday, which contains information about something. The major challenge is to find the right video and understand the correct content, because there are lot of videos available some videos will contain useless content and even though the perfect content available that content should be required to us. If we not found right one it wastes your full effort and full time to extract the correct usefull information. We propose an innovation idea which uses NLP processing for text extraction and BERT Summarization for Text Summarization. This provides a video main content in text description and abstractive summary, enabling users to discriminate between relevant and irrelevant information according to their needs. Furthermore, our experiments show that the joint model can attain good results with informative, concise, and readable multi-line video description and summary in a human evaluation.
ISSN:2267-1242
2555-0403
2267-1242
DOI:10.1051/e3sconf/202339904015