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R. Girardi, “Guiding Ontology Learning and Population by Knowledge System Goals,” Proceedings of In-ternational Conference on Knowledge Engineering and On-tology Development, Education INSTIIC, Valence, 2010, pp. 480-484.

has been cited by the following article:

• TITLE: A Process for Extracting Non-Taxonomic Relationships of Ontologies from Text

  AUTHORS: Ivo Serra, Rosario Girardi

  KEYWORDS: Ontology, Ontology Learning, Non-Taxonomic Relationships, Natural Language Processing

  JOURNAL NAME: Intelligent Information Management, Vol.3 No.4, July 15, 2011

  ABSTRACT: Manual construction of ontologies by domain experts and knowledge engineers is an expensive and time consuming task so, automatic and/or semiautomatic approaches are needed. Ontology learning looks for identifying ontology elements like non-taxonomic relationships from information sources. These relationships correspond to slots in a frame-based ontology. This article proposes an initial process for semiautomatic extraction of non-taxonomic relationships of ontologies from textual sources. It uses Natural Language Processing (NLP) techniques to identify good candidates of non-taxonomic relationships and a data mining technique to suggest their possible best level in the ontology hierarchy. Once the extraction of these relationships is essentially a retrieval task, the metrics of this field like recall, precision and f-measure are used to perform evaluation.