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.
The package was created as part of a project by the University of Pittsburgh Office of Technology Management, and was hosted from 2007 to 2015 on code.google.com/p/semanticvectors
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 other institutions and individuals.
Contributions are welcome (and reasonably frequent).