Title :
Application of data mining in fault diagnosis based on ontology
Author :
Hou, Xiangdan ; Gu, Junhua ; Shen, Xueqin ; Yan, Weili
Author_Institution :
Univ. of Technol., Tianjin, China
Abstract :
In this paper, a new kind of automated fault diagnosis algorithm is proposed. It is a new data-mining algorithm with ontology-based. This algorithm doesn´t only find low-level rules which usually not interesting , but also can find high-level rules which described by high-level concepts. In this paper, we use ontologies provide a mechanism, in data mining, by which domain specific knowledge may be included to aid the discovery process and can find multi-level classification rules, the rules are described by high-level concepts. So it can provide more interesting rules for enterprise. Finally, a study case is given to explain the practical application with the fault diagnosis bases on ontology, and is given encouraging results.
Keywords :
data mining; fault diagnosis; ontologies (artificial intelligence); automated fault diagnosis algorithm; data mining; domain specific knowledge; high-level rules; multi-level classification rules; ontology; Algorithm design and analysis; Association rules; Data analysis; Data mining; Databases; Fault diagnosis; Information analysis; Machine learning algorithms; Ontologies; Research and development;
Conference_Titel :
Information Technology and Applications, 2005. ICITA 2005. Third International Conference on
Print_ISBN :
0-7695-2316-1
DOI :
10.1109/ICITA.2005.70