Chrysoula Gkonela

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In this paper, we present a user-based event detection method for social web videos. Previous research in event detection has focused on content-based techniques, such as pattern recognition algorithms that attempt to understand the contents of a video. There are few user-centric approaches that have considered either search keywords, or external data such(More)
In this paper, we present a system that facilitates the analysis of user activity within a web video. Previous research in user-based techniques has assumed an extra effort from the users, such as video replies, comments, tags, and annotations. We have developed and evaluated the SocialSkip system, which improves sense making of web videos by visualizing(More)
In this paper, we propose a user-based video-indexing method, that automatically generates thumbnails of the most important scenes of an online video stream, by analyzing users’ interactions with a web video player. As a test bench to verify our idea we have extended the YouTube video player into the VideoSkip system. In addition, VideoSkip uses a(More)
In this paper, we propose a user-based video-indexing method, that automatically generates thumbnails of the most important scenes of an online video stream, by analyzing users’ interactions with a web video player. As a test bench to verify our idea we have extended the YouTube video player into the VideoSkip system. In addition, VideoSkip uses a(More)
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