Classified Ranking of Semantic Content Filtered Output Using Self-organizing Neural Networks

  • Marios Angelides
  • Anastasis Sofokleous
  • Minaz Parmar
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4132)


Cosmos-7 is an application that can create and filter MPEG-7 semantic content models with regards to objects and events, both spatially and temporally. The results are presented as numerous video segments that are all relevant to the user’s consumption criteria. These results are not ranked to the user’s ranking of relevancy, which means the user must now laboriously sift through them. Using self organizing networks we rank the segments to the user’s preferences by applying the knowledge gained from similar users’ experience and use content similarity for new segments to derive a relative ranking.


Semantic Content Collaborative Filter Video Segment Similar User Filter Criterion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Marios Angelides
    • 1
  • Anastasis Sofokleous
    • 1
  • Minaz Parmar
    • 1
  1. 1.Brunel UniversityUxbridge, LondonUK

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