Multimedia news exploration and retrieval by integrating keywords, relations and visual features

  • Authors:
  • Hangzai Luo;Jianping Fan;Youjie Zhou

  • Affiliations:
  • Shanghai Key Laboratory of Trustworthy Computing, East China Normal University, Shanghai, China;Department of Computer Science, University of North Carolina-Charlotte, Charlotte, USA;Department of Computer Science, University of North Carolina-Charlotte, Charlotte, USA

  • Venue:
  • Multimedia Tools and Applications
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

Multimedia news may be organized by the keywords and categories for exploration and retrieval applications, but it is very difficult to integrate the relation and visual information into the traditional category browsing and keyword-based search framework. This paper propose a new semantic model that can integrate keyword, relation and visual information in a uniform framework. Based on this semantic representation framework, the news exploration and retrieval applications can be organized by not only keywords and categories but also relations and visual properties. We also proposed a set of algorithms to automatically extract the proposed semantic model automatically from large collection of multimedia news reports.