Title
Classified ranking of semantic content filtered output using self-organizing neural networks
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.
Year
DOI
Venue
2006
10.1007/11840930_6
ICANN (2)
Keywords
Field
DocType
neural network,user experience,self organization
Similitude,Scale-invariant feature transform,Collaborative filtering,Ranking,Computer science,Self-organizing network,Artificial intelligence,Artificial neural network,Semantics,Machine learning,Image compression
Conference
Volume
ISSN
ISBN
4132
0302-9743
3-540-38871-0
Citations 
PageRank 
References 
3
0.39
12
Authors
3
Name
Order
Citations
PageRank
Marios C. Angelides132150.73
Anastasis A. Sofokleous2658.90
Minaz J. Parmar331.41