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There are many practical applications where learning from single class examples is either, the only possible solution, or has a distinct performance advantage. The first case occurs when obtaining examples of a second class is difficult, e.g., classifying sites of "interest" based on web accesses. The second situation is exemplified by the gene knock-out(More)
Lexicon entry1: Data: The Lexical Access Problem consists of determining the intended sequence of words corresponding to an input sequence of phonemes (basic speech sounds) that come from a low-level phoneme recognizer. In this paper we present an information-theoretic approach based on the Minimum Message Length Criterion for solving the Lexical Access(More)
We investigate the effect of paraphrase generation on document retrieval performance. Specifically, we describe experiments where three information sources are used to generate lexical paraphrases of queries posed to the In-ternet. These information sources are: WordNet, a Webster-based thesaurus, and a combination of Webster and WordNet. Corpus-based(More)
In this paper, we present a new co-training strategy that makes use of unlabelled data. It trains two predictors in parallel, with each predictor labelling the unlabelled data for training the other predictor in the next round. Both predictors are support vector machines, one trained using data from the original feature space, the other trained with new(More)