In the case of high dimensionality and data sparseness, words are grouped into a smaller number of (unnamed) concepts using some matrix factorization technique (e.g., SVD) or some clustering method (Pereira, Tishby, and Lee 1993).
words are grouped together based on their distributional properties instead of their explicit semantic/ontological properties.