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In this paper, we present a novel approach to Web search result clustering based on the au- tomatic discovery of word senses from raw text, a task referred to as …...

AbstractUnsupervised methods gain more and more attention nowadays in information extraction area, which allows to design more open extraction systems. In the domain of unsupervised information extraction, clustering methods are …...

We present an effective modification of the popular Brown et al. 1992 word clustering algorithm, using a dependency language model. By leveraging syntax-based context, resulting clusters are better when evaluated …...