UNIGE document Chapitre d'actes
previous document  unige:47671  next document
add to browser collection
Title

Semantic clustering of images using patterns of relevance feedback

Authors
Published in 6th International Workshop on Content-based Multimedia Indexing (CBMI08). London (UK) - Jun 18-20 - IEEE. 2008, p. 323-329
Abstract User-supplied data such as browsing logs, click-through data, and relevance feedback judgements are an important source of knowledge during semantic indexing of documents such as images and video. Low-level indexing and abstraction methods are limited in the manner with which semantic data can be dealt. In this paper and in the context of this semantic data, we apply latent semantic analysis on two forms of user-supplied data, real-world and artificially generated relevance feedback judgements in order to examine the validity of using artificially generated interaction data for the study of semantic image clustering.
Keywords Image clusteringlatent semantic analysislongterm learningrelevance feedback
Identifiers
Full text
Structures
Research groups Computer Vision and Multimedia Laboratory
Viper group
Citation
(ISO format)
MORRISON, Donn Alexander, MARCHAND-MAILLET, Stéphane, BRUNO, Eric. Semantic clustering of images using patterns of relevance feedback. In: 6th International Workshop on Content-based Multimedia Indexing (CBMI08). London (UK). [s.l.] : IEEE, 2008. p. 323-329. https://archive-ouverte.unige.ch/unige:47671

217 hits

0 download

Update

Deposited on : 2015-03-06

Export document
Format :
Citation style :