Title :
Redundant instances and incorrect instances detection mechanism in ontology population
Author :
Xiaoyun Wang ; Jianping Yao ; Haocheng Wang
Author_Institution :
Manage. Sci. & Eng., HangZhou DianZi Univ., Hangzhou, China
Abstract :
With the rapid development of the Internet, many researchers have been focused on ontology knowledge bases updating. Ontology population has played an important role in updating ontology knowledge bases. However, most domestic and foreign scholars focus on the process of ontology population, while neglecting how to detect and eliminate redundant instances and how to detect the results of population. In this paper, we proposed a mechanism based on instance matching algorithm, trying to verify the results of population, we also present an empirical analysis to verify the validity of the method.
Keywords :
Internet; knowledge based systems; ontologies (artificial intelligence); Internet; incorrect instance detection mechanism; instance matching algorithm; ontology knowledge base updating; ontology population; redundant instance detection mechanism; Accuracy; Data mining; Ontologies; Semantic Web; Semantics; Sociology; Statistics; Ontology population; instance matching; redundant instance;
Conference_Titel :
Computer Systems and Industrial Informatics (ICCSII), 2012 International Conference on
Conference_Location :
Sharjah
Print_ISBN :
978-1-4673-5155-3
DOI :
10.1109/ICCSII.2012.6454616