New (old) paper: A Modular Framework to Learn Seed Ontologies from Text
[This is post number 2 of the "2012 publications" series. Read here if you want to know more about this]
I have posted a new publication in the Research page:
Davide Eynard, Matteo Matteucci, and Fabio Marfia (2012).A Modular Framework to Learn Seed Ontologies from Text
"Ontologies are the basic block of modern knowledge-based systems; however the effort and expertise required to develop them are often preventing their widespread adoption. In this chapter we present a tool for the automatic discovery of basic ontologies –we call them seed ontologies– starting from a corpus of documents related to a specific domain of knowledge. These seed ontologies are not meant for direct use, but they can be used to bootstrap the knowledge acquisition process by providing a selection of relevant terms and fundamental relationships. The tool is modular and it allows the integration of different methods/strategies in the indexing of the corpus, selection of relevant terms, discovery of hierarchies and other relationships among terms. Like any induction process, also ontology learning from text is prone to errors, so we do not expect from our tool a 100% correct ontology; according to our evaluation the result is more close to 80%, but this should be enough for a domain expert to complete the work with limited effort and in a short time".
This work is part of the book "Semi-Automatic Ontology Development: Processes and Resources" edited by Maria Teresa Pazienza and Armando Stellato.