Mash-up approach for web video category recommendation

Yi Cheng Song, Haojie Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With the advent of web 2.0, billions of videos are now freely available online. Meanwhile, rich user generated information for these videos such as tags and online encyclopedia offer us a chance to enhance the existing video analysis technologies. In this paper, we propose a mash-up framework to realize video category recommendation by leveraging web information from different sources. Under this framework, we build a web video dataset from the YouTube API, and construct a concept collection for web video category recommendation (CCWV-CR) from this dataset, which consists of the web video concepts with small semantic gap and high categorization distinguishability. Besides, Wikipedia Propagation is proposed to optimize the video similarity measurement. The experiments on the large-scale dataset with 80,031 web videos demonstrate that: (1) the mash-up category recommendation framework has a great improvement than the existing state-of-art methods. (2) CCWV-CR is an efficient feature space for video category recommendation. (3) Wikipedia Propagation could boost the performance of video category recommendation.

Original languageEnglish (US)
Title of host publicationProceedings - 4th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2010
Pages197-202
Number of pages6
DOIs
StatePublished - Dec 1 2010
Event4th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2010 - Singapore, Singapore
Duration: Nov 14 2010Nov 17 2010

Publication series

NameProceedings - 4th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2010

Other

Other4th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2010
CountrySingapore
CitySingapore
Period11/14/1011/17/10

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  • Cite this

    Song, Y. C., & Li, H. (2010). Mash-up approach for web video category recommendation. In Proceedings - 4th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2010 (pp. 197-202). [5673984] (Proceedings - 4th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2010). https://doi.org/10.1109/PSIVT.2010.40