Abstract
This paper presents a technique to automatically derive ontologies which is based on hierarchical clustering of document corpora. The procedure applies to a set of texts forming a domain document corpus and creates a hierarchical structure (tree) where at every node is associated a set of terms derived from the document feature vectors. The labeling of the cluster is made by using a new algorithm presented in this work. The derived terms may represent concepts candidate to build a domain taxonomy from which the hierarchical relationships among the classes of the domain ontology can be extracted. To test the technique shown, has been built a propotype tool named (OntoClust).
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Di Martino, B., Cantiello, P. (2009). Automatic Ontology Extraction with Text Clustering. In: Papadopoulos, G.A., Badica, C. (eds) Intelligent Distributed Computing III. Studies in Computational Intelligence, vol 237. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03214-1_22
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DOI: https://doi.org/10.1007/978-3-642-03214-1_22
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