A New Approach for Video Concept Detection Based on User Comments

Abstract

Video concept detection means describing a video with semantic concepts that correspond to the content of the video. The concepts
help to retrieve video quickly. These semantic concepts describe high-level elements that depict the key information present in the
content. In recent years, many efforts have been done to automate this task because the manual solution is time-consuming. Nowadays, videos come with comments. Therefore, in addition to the content of the videos, the comments should be analyzed because they contain valuable data that help to retrieve videos. This paper focused especially on videos shared on social media. The specificity of these videos was the presence of massive comments. This paper attempted to exploit comments by extracting concepts from them. This would support the research effort that works only on the visual content. Natural language processing techniques were used to analyze comments and to filter words to retain only the ones that could be considered as concepts. The proposed approach was tested on YouTube videos. The results demonstrated that the proposed approach was able to extract accurate data and concepts from the comments that could be used to ease the retrieval of videos. The findings supported the research effort of working on the visual and audio contents of the videos.