Label ranking studies the problem of learning a mapping from instances to rankings over a predefined set of labels. Hitherto existing approaches to label ranking implicitly operate...
: This paper presents an automatic method and interface to enrich semantically WordNet with categories from general domain classification systems. The method is performed in two co...
The scarcity of manually labeled data for supervised machine learning methods presents a significant limitation on their ability to acquire knowledge. The use of kernels in Suppor...
Mahesh Joshi, Ted Pedersen, Richard Maclin, Sergue...
For manyknowledgeintensive applications, it is necessary to have extensive domain-specific knowledgein addition to general-purpose knowledge bases usually built around MachineRead...
Many real-world sequence learning tasks require the prediction of sequences of labels from noisy, unsegmented input data. In speech recognition, for example, an acoustic signal is...