Semantic taxonomies such as WordNet provide a rich source of knowledge for natural language processing applications, but are expensive to build, maintain, and extend. Motivated by...
Selective sampling, a form of active learning, reduces the cost of labeling training data by asking only for the labels of the most informative unlabeled examples. We introduce a ...
A language-independent framework for syntactic finlte-state parsing is discussed. The article presents a framework, a formalism, a compiler and a parser for grammars written in th...
Kimmo Koskenniemi, Pasi Tapanainen, Atro Voutilain...
Active learners alleviate the burden of labeling large amounts of data by detecting and asking the user to label only the most informative examples in the domain. We focus here on...
Abstract. As XML becomes a popular data representation and exchange format over the web, XML schema design has become an important research area. Formal Concept Analysis (FCA) has ...
Katalin Tunde Janosi-Rancz, Viorica Varga, Timea N...