DocumentCode
3503648
Title
Ontology Based Knowledge Modeling for Structural Engineering Experiment Information Management
Author
Zhang, Xiaohui ; Di, Ruihua ; Liang, Yi
Author_Institution
Sch. of Comput. Sci., Beijing Univ. of Technol., Beijing, China
fYear
2010
fDate
1-5 Nov. 2010
Firstpage
40
Lastpage
45
Abstract
Structural engineering experiment plays an important role in the civil infrastructure design and research. The diversity and heterogeneity of information representation among multiple experimental sites makes the experiment information integration difficult and lead to the poor accuracy when making the keyword matching-based information ret rival. Aiming on this issue, an ontology-based knowledge model called SEKM is proposed in this paper. Based on the domain knowledge, SEKM is composed of the concept model SEDO(Structural Engineering Domain Ontology) and the rule base SERB(Structural Engineering Rule Base), and provide the uniform experiment information representation in the structural engineering field. To enhance the knowledge representation power of SEKM, an evolution-based rule base optimization method is present, which enrich the rule base with the online analysis of the statistical information about SEKM accessing. SEKM is initially implemented based on OWL 2 specification and has been adopted in the experiment information management by Structural Engineering Experimental Center of Beijing University of Technology.
Keywords
information management; ontologies (artificial intelligence); structural engineering computing; OWL 2 specification; SEDO; SEKM; SERB; civil infrastructure design; civil infrastructure research; evolution-based rule base optimization; information management; information representation; knowledge representation; ontology based knowledge modeling; structural engineering domain ontology; structural engineering experiment; structural engineering rule base; knowledge modeling; ontology; structural engineering;
fLanguage
English
Publisher
ieee
Conference_Titel
Grid and Cooperative Computing (GCC), 2010 9th International Conference on
Conference_Location
Nanjing
Print_ISBN
978-1-4244-9334-0
Electronic_ISBN
978-0-7695-4313-0
Type
conf
DOI
10.1109/GCC.2010.21
Filename
5662529
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