Content-Oriented Knowledge Modeling for Automated Parts Library Ontology Merging

Author(s):  
Joonmyun Cho ◽  
Hyun Kim ◽  
Soonhung Han
2014 ◽  
Vol 530-531 ◽  
pp. 407-412
Author(s):  
Yong Hong Luo ◽  
Wei Ming Liu

Fuzzy ontology can be built to effectively deal with uncertainty and ambiguity for domain knowledge modeling. Merging multiple fuzzy local ontologies may implement semantic integration of multiple data sources and semantic interoperability between heterogeneous systems in distributed environment. In order to solve the problem of semantic inconsistency mappings for fuzzy ontology merging system, we proposed a detection algorithm of semantic inconsistency mapping which includes sub detection methods of circular semantic inconsistency, subclass-of axiom redundancy semantic inconsistency, attribute membership semantic inconsistency and disjoint axioms redundancy semantic inconsistency. With the detection algorithm of semantic inconsistency, we establish fuzzy ontology merging system in experiment.


Author(s):  
Shi An ◽  
Pablo Martinez ◽  
Rafiq Ahmad ◽  
Mohamed Al-Hussein
Keyword(s):  

Author(s):  
Abdoul Azize Kindo ◽  
Guidedi Kaladzavi ◽  
Sadouanouan Malo ◽  
Gaoussou Camara ◽  
Theodore Marie Yves Tapsoba ◽  
...  

Author(s):  
Wei Yun ◽  
Xuan Zhang ◽  
Zhudong Li ◽  
Hui Liu ◽  
Mengting Han
Keyword(s):  

2007 ◽  
Vol 96 (3) ◽  
pp. 227-239 ◽  
Author(s):  
Sandra L. Carpenter ◽  
Harry S. Delugach ◽  
Letha H. Etzkorn ◽  
Phillip A. Farrington ◽  
Julie L. Fortune ◽  
...  

Author(s):  
Man Tianxing ◽  
Nataly Zhukova ◽  
Alexander Vodyaho ◽  
Tin Tun Aung

Extracting knowledge from data streams received from observed objects through data mining is required in various domains. However, there is a lack of any kind of guidance on which techniques can or should be used in which contexts. Meta mining technology can help build processes of data processing based on knowledge models taking into account the specific features of the objects. This paper proposes a meta mining ontology framework that allows selecting algorithms for solving specific data mining tasks and build suitable processes. The proposed ontology is constructed using existing ontologies and is extended with an ontology of data characteristics and task requirements. Different from the existing ontologies, the proposed ontology describes the overall data mining process, used to build data processing processes in various domains, and has low computational complexity compared to others. The authors developed an ontology merging method and a sub-ontology extraction method, which are implemented based on OWL API via extracting and integrating the relevant axioms.


Author(s):  
Baolong Zhang ◽  
Xiangqian Wang ◽  
Huizong Li ◽  
Miaomiao Jiang

Sign in / Sign up

Export Citation Format

Share Document