Probabilistic approaches to part-of-speech (POS) tagging compile statistics from massive corpora such as the Lancaster-Oslo-Bergen (LOB) corpus. Training on a 900,000 token training corpus, the hidden Markov model (HMM) method easily achieves a 95 per cent success rate on a 100,000 token test corpus. However, even such large corpora contain relatively few words and new words are subsequently en...

It is likely in real-world applications that only little data is available for training a knowledge-based system. We present a method for automatically training the knowledge-representing membership functions of a Fuzzy-Pattern-Classification system that works also when only little data is available and the universal set is described insufficiently. Actually, this paper presents how the Modifie...

The problem of generalization in neural networks, that is, how well a network will perform on unseen data, is has received much attention recently. In this paper we present an approach to generating learning algorithms which have the potential to generalize from very small training sets. We believe that in this paper outlines a new, although potentially computationally expensive, approach to op...