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IEEE/ICACT20240357 Slide.13        [Big Slide]	Oral Presentation
	In this study, we use a YOLO deep learning model to extract objects from videos frame by frame to develop a metadata expansion-based search and recommendation system. At the same time, we extract speech from the video separately and convert it into a script using STT technology. The extracted script data is then segmented into scenes. Then, we synchronize the object and text data to create a single contextual data. We check whether the context data is appropriate for the video and fine-tune it by making adjustments. Index the generated contextual data by grouping it with the video. Expand the metadata based on the indexed information. Include the expanded metadata in search or recommendation to improve the performance of the search and recommendation system.

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