The Application of Singular Value Decomposition to Dutch Noun-Adjective Matrices
Tim Van de Cruys, P. Mertens · University of Groningen research database (University of Groningen / Centre for Information Technology) · 2006
Automatic acquisition of semantics from text has received quite some attention in natural language processing. A lot of research has been done by looking at syntactically similar contexts. For example, semantically related nouns can be clustered by looking at the collocating adjectives. There are, however, two major problems with this approach : computational complexity and data sparseness. This paper describes the application of a mathematical technique called singular value decomposition, which has been succesfully applied in Information Retrieval to counter these problems. It is investigated whether this technique is also able to cluster nouns according to latent semantic dimensions in a reduced adjective space.