• Complex
  • Title
  • Keyword
  • Abstract
  • Scholars
  • Journal
  • ISSN
  • Conference
搜索

Author:

Zhang, Xiaohui (Zhang, Xiaohui.) | Di, Ruihua (Di, Ruihua.) | Liang, Yi (Liang, Yi.)

Indexed by:

EI Scopus

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 retrival. 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. © 2010 IEEE.

Keyword:

Ontology Information management Knowledge representation Structural design

Author Community:

  • [ 1 ] [Zhang, Xiaohui]School of Computer Science, Beijing University of Technology, BJUT, Beijing, China
  • [ 2 ] [Di, Ruihua]School of Computer Science, Beijing University of Technology, BJUT, Beijing, China
  • [ 3 ] [Liang, Yi]School of Computer Science, Beijing University of Technology, BJUT, Beijing, China

Reprint Author's Address:

Show more details

Related Keywords:

Related Article:

Source :

Year: 2010

Page: 40-45

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 5

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

Affiliated Colleges:

Online/Total:670/5312184
Address:BJUT Library(100 Pingleyuan,Chaoyang District,Beijing 100124, China Post Code:100124) Contact Us:010-67392185
Copyright:BJUT Library Technical Support:Beijing Aegean Software Co., Ltd.