A Process for Extracting Non-Taxonomic Relationships of Ontologies from Text
Ivo Serra, Rosario Girardi
DOI: 10.4236/iim.2011.34014   PDF    HTML     6,068 Downloads   10,796 Views   Citations


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.

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I. Serra and R. Girardi, "A Process for Extracting Non-Taxonomic Relationships of Ontologies from Text," Intelligent Information Management, Vol. 3 No. 4, 2011, pp. 119-124. doi: 10.4236/iim.2011.34014.

Conflicts of Interest

The authors declare no conflicts of interest.


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