Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/32077

TitleEvaluating techniques for learning non-taxonomic relationships of ontologies from text
Author(s)Serra, Ivo
Girardi, Rosário
Novais, Paulo
KeywordsLearning non-taxonomic relationships
Ontology
Ontology learning
Natural language processing
Machine learning
Issue date2014
PublisherElsevier
JournalExpert systems with applications
Abstract(s)Learning Non-Taxonomic Relationships is a sub-field of Ontology Learning that aims at automating the extraction of these relationships from text. Several techniques have been proposed based on Natural Language Processing and Machine Learning. However just like for other techniques for Ontology Learning, evaluating techniques for Learning Non-Taxonomic Relationships is an open problem. Three general proposals suggest that the learned ontologies can be evaluated in an executable application or by domain experts or even by a comparison with a predefined reference ontology. This article proposes two procedures to evaluate techniques for Learning Non-Taxonomic Relationships based on the comparison of the relationships obtained with those of a reference ontology. Also, these procedures are used in the evaluation of two state of the art techniques performing the extraction of relationships from two corpora in the domains of biology and Family Law.
TypeArticle
Description"Manuscript"
URIhttp://hdl.handle.net/1822/32077
DOI10.1016/j.eswa.2014.02.042
ISSN0957-4174
Publisher versionhttp://www.sciencedirect.com/science/article/pii/S0957417414001183
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CCTC - Artigos em revistas internacionais

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