| Popis: |
To improve the retrieval accuracy of content-based video retrieval systems, researchers face a hard challenge that is reducing the 'semantic gap' between the extracted features of the systems and the richness of human semantics. This paper presents a novel video retrieval system to bridge the semantic gap. Firstly, the video captions are segmented from the video and then are transformed into text format. To extract the semantic information from the video streaming we apply a text mining process, which adopts a cluster algorithm as a kernel, on the text format captions. On the other hand, in this system, users are requested to comment on the video which they download from the system when they have watched the video. Then we associate the users' comments with the video on the system. The same text mining process is used to deal with the comment texts. We combine the captions of the video with the comments on the video to extract the semantic information of the video more accurately. Finally, taking advantage of the comments and the captions of the video, we performed experiments on a set of videos and obtained promising results. |
