Abstract
Distribution information plays an important role in word categorization. In this paper, we present a novel distributional model, distributional lattices to discover syntactic categories in child directed speech. A distributional lattice is a hierarchy formed by closed sets of words that are distributionally similar. Such a hierarchy is potentially useful for capturing syntactic categories by clustering words with associate patterns they occur in. In order to empirically support the suggestion that the distributional lattice is effective at categorizing words, we present a distributional lattice analysis of the Brent corpus of child-directed speech. The results show that distributional lattices are able to yield extremely accurate syntactic categories.
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