This paper proposes the use of uncertainty reduction in machine learning methods such as co-training and bilingual bootstrapping, which are referred to, in a general term, as ‘c...
A central problem of word sense disambiguation (WSD) is the lack of manually sense-tagged data required for supervised learning. In this paper, we evaluate an approach to automati...
We present a supervised machine learning algorithm for metonymy resolution, which exploits the similarity between examples of conventional metonymy. We show that syntactic head-mo...
Data mining focuses on the development of methods and algorithms for such tasks as classification, clustering, rule induction, and discovery of associations. In the database fiel...
In Information Systems research there are a growing number of studies that must necessarily draw upon the contexts, experiences and narratives of practitioners. This calls for res...