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.