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Dimensional Reduction in Vector Space Methods for Natural Language Processing: Products and Projections

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Abstract

We introduce vector space based approaches to natural language processing and some of their similarities with quantum theory when applied to information retrieval. We explain how dimensional reduction is called for from both a practical and theoretical point of view and how this can be achieved through choice of product or through projectors onto subspaces.

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  1. Center Leo Apostel for Interdisciplinary Studies (CLEA), Brussels Free University, Pleinlaan 2, 1050, Brussels, Belgium

    Sven Aerts

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  1. Sven Aerts
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Aerts, S. Dimensional Reduction in Vector Space Methods for Natural Language Processing: Products and Projections. Int J Theor Phys 50, 3646–3653 (2011). https://doi.org/10.1007/s10773-011-0851-6

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  • DOI: https://doi.org/10.1007/s10773-011-0851-6

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