کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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387997 | 660915 | 2009 | 7 صفحه PDF | دانلود رایگان |
Ontology learning (OL) from texts has been suggested as a technology that helps to reduce the bottleneck of knowledge acquisition in the construction of domain ontologies. In this learning process, the discovery, and possibly also labeling, of non-taxonomic relationships has been identified as one of the most difficult and often neglected problems. In this paper, we propose a technique that addresses this issue by analyzing a domain text corpus to extract verbs frequently applied for linking certain pairs of concepts. Integrated in an ontology building process, this technique aims to reduce the work-load of knowledge engineers and domain experts by suggesting candidate relationships that might become part of the ontology as well as prospective labels for them.
Journal: Expert Systems with Applications - Volume 36, Issue 7, September 2009, Pages 10288–10294