Classified ranking of semantic content filtered output using self-organizing neural networks

Authors:
Marios Angelides;Anastasis Sofokleous;Minaz Parmar
Affiliations:
Brunel University, Uxbridge, London, UK;Brunel University, Uxbridge, London, UK;Brunel University, Uxbridge, London, UK
Venue:
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Year:
2006

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Abstract

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.