Multimedia data mining and searching through dynamic index evolution

  • Authors:

  • Clement Leung;Jiming Liu

  • Affiliations:

  • Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong;Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong

  • Venue:
  • VISUAL'07 Proceedings of the 9th international conference on Advances in visual information systems
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

Abstract

While the searching of text document has grown relatively mature on the Internet, the searching of images and other forms of multimedia data significantly lags behind. To search visual information on the basis of semantic concepts requires both their discovery and meaningful indexing. By analyzing the users' search, relevance feedback and selection patterns, we propose a method which allows semantic concepts to be discovered and migrated through an index hierarchy. Our method also includes a robust scoring mechanism that permits faulty indexing to be rectified over time. These include: (i) repeated and sustained corroboration of specific index terms before installation, and (ii) the ability for the index score to be both incremented and decremented. Experimental results indicate that convergence to an optimum index level may be achieved in reasonable time periods through such dynamic index evolution.