Computer Science ›› 2016, Vol. 43 ›› Issue (3): 213-219.doi: 10.11896/j.issn.1002-137X.2016.03.039

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Automatic Ontology Population Based on Heuristic Rules

LI Yi-xiao, LI Hong-wei, SHEN Li-wei and ZHAO Wen-yun   

  • Online:2018-12-01 Published:2018-12-01

Abstract: The cycle of building ontology can be shortened by means of automatically extracting domain ontology in Internet resources,but automatic ontology population is still a challenge in ontology engineering.There are two difficulties in this area,which are how to extract terms and how to construct the mapping relationship between the new terms and the existed ontology.Therefore,this paper proposed a method for automatic ontology population based on the proposed heuristic rules.This method extracts natural language texts from the Internet,combines traditional natural language processing methods for text preprocessing,discovers domain terms by preferentially matching object properties,enriches the ontology by matching these terms using heuristic rules,and finally checks the consistency of the enriched ontology.On the base of the proposed method,this paper also implemented a Web-based tool for ontology population.Using an urban landscape information core ontology as a case study,the experimental results show that the method for enriching ontology individuals has a high precision and recall.The results also prove that the proposed method is effective and feasible.

Key words: Ontology population,Domain ontology,Term extraction,Heuristic rule

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