… It usually involves a multi-class multi-label classification problem. To solve this problem, …
a novel approach, ontology based supervised learning for multi-label image annotation, where …

… 25, an ontology-based supervised learning for multi-label image … , we propose, in this paper,
to adopt our previous classiŻcation method for image annotation. Our motivation is to exploit …

… on ontologies (tools, economic ontologies), multi-label classification and text classification …
our construction of the ontology of economics using a semi-automatic ontology tool and other …

… The obtained features are used for object classification. The assumption is that … for image
annotation, so multi-label classification methods are used. The result of the image classification …

… and how to best use ontology in semantic representation and … problem of image semantic
annotation using ontology and … multi label image annotation. In all segmentation methods, an …

… the conventional flat multi-label classification approach. Furthermore, our … -based classification
is capable of suggesting annotations that are semantically close to the true annotations. …

… , we propose a novel approach, ontology based supervised learning for multi-label image …
technique for multilabel image annotation by leveraging the cheaply gathered web images. In …

… image annotation task as a Multi-Label Classification (MLC) problem, in which each
image can … While most of automatic image annotation (AIA) models make use of the co-occurrence …

… , 4 multilabel algorithms and 3 image annotation data sets suggest … the training time of
standard multi-label algorithms, particularly in … information on multi-label classification, including …

… -knowledge based intelligent system for image annotation, … knowledge and can annotate
images with concepts on different … use multi-label learning for solving the problem of annotating …