Combining vector space model and category hierarchy model for TV content similarity measure

Zhiwen Yu, Xingshe Zhou

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

In this paper, we propose a new approach for TV content similarity measure, which combines both vector space model and category hierarchy model. The hybrid measure proposed here makes the most of TV metadata information and takes advantage of the two similarity measurements. It measures TV content similarity from the semantic level other than the physical level. Furthermore, we propose an adaptive strategy for setting the combination parameters. The experimental results showed that using the combining approach proposed here is superior to using either similarity measure alone for example-based retrieval of TV content.

Original languageEnglish
Title of host publication3rd International Conference on Multimedia and Ubiquitous Engineering, MUE 2009
Pages130-136
Number of pages7
DOIs
StatePublished - 2009
Event3rd International Conference on Multimedia and Ubiquitous Engineering, MUE 2009 - Qingdao, China
Duration: 4 Jun 20096 Jun 2009

Publication series

Name3rd International Conference on Multimedia and Ubiquitous Engineering, MUE 2009

Conference

Conference3rd International Conference on Multimedia and Ubiquitous Engineering, MUE 2009
Country/TerritoryChina
CityQingdao
Period4/06/096/06/09

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