Neural networks: a systematic introduction
Neural networks: a systematic introduction
ACM Computing Surveys (CSUR)
Content-based filtering and personalization using structured metadata
Proceedings of the 2nd ACM/IEEE-CS joint conference on Digital libraries
Semantic Annotation of Sports Videos
IEEE MultiMedia
MPEG-7: Overview of MPEG-7 Description Tools, Part 2
IEEE MultiMedia
Web mining for web personalization
ACM Transactions on Internet Technology (TOIT)
Content-based image retrieval by using tree-structured features and multi-layer self-organizing map
Pattern Analysis & Applications
Personalized Digital Item Adaptation in Service-Oriented Environments
SMAP '06 Proceedings of the First International Workshop on Semantic Media Adaptation and Personalization
Competing Behavior of Two Kinds of Self-Organizing Maps and Its Application to Clustering
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Using MPEG-7 and MPEG-21 for Personalizing Video
IEEE MultiMedia
Using image segments in PicSOM CBIR system
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
Classified ranking of semantic content filtered output using self-organizing neural networks
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
A sober look at clustering stability
COLT'06 Proceedings of the 19th annual conference on Learning Theory
Semantic annotation of image groups with self-organizing maps
CIVR'05 Proceedings of the 4th international conference on Image and Video Retrieval
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COSMOS-7 models semantic content in MPEG-7 such as objects and events and their spatio-temporality. When a user queries a COSMOS-7 model, the output is usually presented as a sequence of relevant, albeit unranked, video segments through which the user must sift. In this paper, we report how we use Self-Organising Neural Networks (SONNs) to cluster and rank the video segments through consideration of user preferences and knowledge gained from usage of the same content by similar users and of similar content by the same user.