Tag transformer

Yicheng Song, Juan Cao, Zhineng Chen, Yongdong Zhang, Jintao Li

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

3 Scopus citations

Abstract

Human annotations (titles and tags) of web videos facilitate most web video applications. However, the raw tags are noisy, sparse and structureless, which limit the effectiveness of tags. In this paper, we propose a tag transformer schema to solve these problems. We first eliminate those imprecise and meaningless tags with Wikipedia, and then transform the remaining tags to the Wikipedia category set to gather a precise, complete and structural description of the tags. Our experimental results on web video categorization demonstrate the superiority of the transformed space. We also apply tag transformer into the first study of using Wikipedia category system to structurally recommend the related videos. The online user study of the demo system suggests that our method could bring fantastic experience to the web users.

Original languageEnglish (US)
Title of host publicationMM'10 - Proceedings of the ACM Multimedia 2010 International Conference
Pages639-642
Number of pages4
DOIs
StatePublished - Dec 1 2010
Event18th ACM International Conference on Multimedia ACM Multimedia 2010, MM'10 - Firenze, Italy
Duration: Oct 25 2010Oct 29 2010

Publication series

NameMM'10 - Proceedings of the ACM Multimedia 2010 International Conference

Other

Other18th ACM International Conference on Multimedia ACM Multimedia 2010, MM'10
CountryItaly
CityFirenze
Period10/25/1010/29/10

Keywords

  • online user study
  • structural web video recommendation
  • tag cleaning
  • tag transformer
  • wikipedia category tree

Cite this