SemanticVectors creates semantic WordSpace models from free natural language text. Such models are designed to represent words and documents in terms of underlying concepts. They can be used for many semantic (concept-aware) matching tasks such as automatic thesaurus generation, knowledge representation, and concept matching.

See for instructions.

The package was created as part of a project by the University of Pittsburgh Office of Technology Management in 2007, and has been through several phases on and github since.

It has been developed and maintained by contributors from the University of Texas, Queensland University of Technology, the Austrian Research Institute for Artificial Intelligence, Google Inc., and several other institutions and individuals.

Contributions are welcome.