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The S-Space Package is a collection of algorithms for building Semantic Spaces. These algorithms process text corpora and map semantic representations for words onto high dimensional vectors. These approaches are known by many names, such as word spaces, semantic spaces, or distributed semantics. ... [More] The research and development is being done by the Natural Language Processing group at UCLA led by David Jurgens and Keith Stevens, under the advisory of Dr. Michael Dyer. Our initial goal is to provide a uniform implementation for many common semantic space algorithms in order to facilitate researc [Less]

Basic text to numbers tokenizer for machine learning. Tokkens makes it easy to apply a vector space model to text documents, targeted towards with machine learning. It provides a mapping between numbers and tokens (strings).