2020 IEEE International Symposium on Multimedia (ISM) 2020
DOI: 10.1109/ism.2020.00034
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A Clustering-Based Method for Automatic Educational Video Recommendation Using Deep Face-Features of Lecturers

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Cited by 2 publications
(4 citation statements)
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“…As part of this method, we also define an algorithm for finding an adequate number of clusters based on the silhouette score. We investigate to what extent this method can be used as the core to leverage and enhance some innovative applications, especially in three different practical and important tasks: Video Face Recognition [2], Educational Video Recommendation [4], and Subtitles Positioning in 360-Video [3].…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…As part of this method, we also define an algorithm for finding an adequate number of clusters based on the silhouette score. We investigate to what extent this method can be used as the core to leverage and enhance some innovative applications, especially in three different practical and important tasks: Video Face Recognition [2], Educational Video Recommendation [4], and Subtitles Positioning in 360-Video [3].…”
Section: Discussionmentioning
confidence: 99%
“…It is important to notice that our method is unsupervised and does not require the information of the lecturers in advance. We have also published these results in a relevant multimedia conference[4].…”
mentioning
confidence: 94%
“…However, this method can be used in a hybrid recommendation approach, that combines both textual and audiovisual information from the video to create clusters. The results of this application were published at relevant multimedia conference (63). Video Face Clustering for Subtitles Positioning in 360-Videos In (64), we proposed an authoring model for interactive 360-video.…”
Section: Discussionmentioning
confidence: 99%
“…As a result of this research, three papers have already been published at relevant multimedia conferences (62,63,64). In (62), we have evaluated video face clustering together with a cluster-matching method for video face recognition.…”
Section: Publicationsmentioning
confidence: 99%