Learning prototype ontologies by hierachical latent semantic analysis

An ontology is a specification of a conceptualization. For a newly evolving domain often no concept hierarchy exists. In this paper we describe a text clustering approach, which is not only able to extract concepts from a text collection in an automatic fashion, but also generates a hierarchy of concepts. It uses a probabilistic model, relating words to documants and concepts.