DocumentCode
3497412
Title
A Domain Adaptive Ontology Learning Framework
Author
Nie, Xuejun ; Zhou, Jingli
Author_Institution
Huazhong Univ. of Sci. & Technol., Wuhan
fYear
2008
fDate
6-8 April 2008
Firstpage
1726
Lastpage
1729
Abstract
Ontology leaning is a solution to the bottleneck of knowledge acquisition and time-consuming construction of ontologies. In recent years, a lot of research work has been done to design appropriate methods for ontology learning. However, all these methods suffer from some common shortcomings which prevent wide production and usage of ontologies. In this paper, we first analyze the characteristics of these shortcomings and then proposed an ontology learning framework OntoExtractor, which includes seed concept extraction, semantic relationships construction and ontology refinement. As the result shows, this framework could provide good domain adaptability for ontology learning system.
Keywords
knowledge acquisition; learning systems; ontologies (artificial intelligence); OntoExtractor; domain adaptability; domain adaptive ontology learning; knowledge acquisition; ontology learning system; ontology refinement; seed concept extraction; semantic relationships construction; Buildings; Data mining; Design methodology; Information analysis; Instruments; Knowledge acquisition; Learning systems; Ontologies; Production; Semantic Web;
fLanguage
English
Publisher
ieee
Conference_Titel
Networking, Sensing and Control, 2008. ICNSC 2008. IEEE International Conference on
Conference_Location
Sanya
Print_ISBN
978-1-4244-1685-1
Electronic_ISBN
978-1-4244-1686-8
Type
conf
DOI
10.1109/ICNSC.2008.4525501
Filename
4525501
Link To Document