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Emergence of Linguistic Representations by Independent Component Analysis

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A72. Helsinki University of Technology, Laboratory of Computer and Information Science, Espoo, Finland, (2003)

Abstract

Our aim is to find syntactic and semantic relationships and roles of words based on the analysis of corpora. We study three methods for analyzing words in contexts as potential methods for solving this task. The methods are latent semantic analysis, self-organizing map and independent component analysis. Latent semantic analysis is a simple method for automatic generation of concepts that are useful, e.g., in encoding documents for information retrieval purposes. However, these concepts cannot easily be interpreted by humans. Self-organizing maps can be used to generate an explicit diagram which characterizes the relationships between words. A word map reflects syntactic categories in the overall organization and semantic categories in the local level. The self-organizing map does not, however, provide any explicit distinct categories for the words. The emergent syntactic and semantic categories are only implicit. Independent component analysis applied on word context data gives distinct features which reflect syntactic and semantic categories. Thus, independent component analysis gives features or categories that are both explicit and can easily be interpreted by humans. This result can be obtained without any human supervision or tagged corpora that would have some predetermined morphological, syntactic or semantic information.

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