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The S-Space Package is a collection of algorithms for building Semantic Spaces as well as a highly-scalable library for designing new distributional semantics algorithms. Distributional algorithms process text corpora and represent the semantic for words as high dimensional feature vectors.
The Semantic Vectors package uses a Random Projection algorithm, a form of automatic semantic analysis. Other methods supported by the package include Latent Semantic Analysis (LSA) and Reflective Random Indexing. Latent Semantic Analysis (LSA) is a theory and method for extracting and representing the contextual-usage meaning of words by statistical computations applied to a large corpus of text. This library is used in semantic analysis and text mining.