Multi-label learning deals with data associated with multiple labels simultaneously. Previous work on multi-label learning assumes that for each instance, the "full" lab...
There has been a lot of research targeting text classification. Many of them focus on a particular characteristic of text data - multi-labelity. This arises due to the fact that a ...
Mohammad Salim Ahmed, Latifur Khan, Nikunj C. Oza,...
Abstract. This paper presents an approach to automatically subject index fulltext documents with multiple labels based on binary support vector machines (SVM). The aim was to test ...
Abstract-- Associative classification is a new classification approach integrating association mining and classification. It becomes a significant tool for knowledge discovery and ...
In this paper, we present the LIP6 annotation models for the ImageCLEFannotation 2010 task. We study two methods to train and merge the results of different classifiers in order to...
Ali Fakeri-Tabrizi, Sabrina Tollari, Nicolas Usuni...