Ontologies are a well-motivated formal representation to model knowledge needed to extract and encode data from text. Yet, their tight integration with Information Extraction (IE)...
Abstract. We analyze the expected cost of a greedy active learning algorithm. Our analysis extends previous work to a more general setting in which different queries have differe...
Learning an unknown halfspace (also called a perceptron) from labeled examples is one of the classic problems in machine learning. In the noise-free case, when a halfspace consist...
Most information extraction (IE) systems identify facts that are explicitly stated in text. However, in natural language, some facts are implicit, and identifying them requires â€...
This is foremost a methodological contribution. It focuses on the foundation of anticipation and the pertinent implications that anticipation has on learning (theory and experiment...