文献类型：期刊文献

英文题名：An Empirical Study of the Textual Content of Online Videos

作者：Chen, Yixin[1];Wang, Wen[1];He, Wenbo[1];Li, Xiaofeng[2]

第一作者：Chen, Yixin

通讯作者：Chen, YX[1]

机构：[1]McGill Univ, Sch Comp Sci, 845 Rue Sherbrooke O, Montreal, PQ H3A 0G4, Canada;[2]Beijing Union Univ, Informat Coll, 97 Beisihuan Rd, Beijing, Peoples R China

第一机构：McGill Univ, Sch Comp Sci, 845 Rue Sherbrooke O, Montreal, PQ H3A 0G4, Canada

通讯机构：[1]corresponding author), McGill Univ, Sch Comp Sci, 845 Rue Sherbrooke O, Montreal, PQ H3A 0G4, Canada.

年份：2016

卷号：10

期号：3

起止页码：323-346

外文期刊名：INTERNATIONAL JOURNAL OF SEMANTIC COMPUTING

收录：WOS:【ESCI(收录号:WOS:000389655900003)】；

语种：英文

外文关键词：Big data; multimedia; textual data

摘要：Fuelled by the advancement in multimedia technologies, users across the world have witnessed the proliferation of online videos. Compared with the visual content of these videos, the textual content, for example, titles, tags, or descriptions, has been more broadly exploited in the real-world video data mining or information retrieval tasks. To enhance the understanding of videos, and improve the performance of the tasks such as automatic video annotation, video clustering, and cross-modal tag cleansing, the textual and visual content of videos are combined, through various methods. However, the absence of an empirical study on the properties of these contents makes them less solid to gain satisfactory performance. Therefore, in this paper, we conduct this study to verify the properties of textual content and draw insights from these analyses to promote further developments in video data mining that combine the two contents.