BOWL: augmenting the Semantic Web with beliefs

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• 作者：Jin Song Dong ; Yuzhang Feng ; Yuan-Fang Li…
• 关键词：Semantic Web ; OWL ; Probabilistic ontology language
• 刊名：Innovations in Systems and Software Engineering
• 出版年：2015
• 出版时间：September 2015
• 年：2015
• 卷：11
• 期：3
• 页码：203-215
• 全文大小：607 KB
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• 作者单位：Jin Song Dong (1)
  Yuzhang Feng (2)
  Yuan-Fang Li (3)
  Colin Keng-Yan Tan (1)
  Bimlesh Wadhwa (1)
  Hai H. Wang (4)
  
  1. School of Computing, National University of Singapore, Computing 1, 13 Computing Drive, Singapore, 117417, Singapore
  2. SAS Institute, Singapore, 20 Anson Rd, Singapore, 079912, Singapore
  3. Faculty of IT, Monash University, Wellington Road, Clayton, VIC, 3800, Australia
  4. School of Engineering and Applied Science, Aston University, Aston Triangle, Birmingham, B4 7ET, UK
  
• 刊物类别：Computer Science
• 刊物主题：Software Engineering
  Computing Methodologies
  Computer Applications
  
• 出版者：Springer London
• ISSN：1614-5054

文摘

As the Semantic Web is an open, complex and constantly evolving medium, it is the norm, but not exception that information at different sites is incomplete or inconsistent. This poses challenges for the engineering and development of agent systems on the Semantic Web, since autonomous software agents need to understand, process and aggregate this information. Ontology language OWL provides core language constructs to semantically markup resources on the Semantic Web, on which software agents interact and cooperate to accomplish complex tasks. However, as OWL was designed on top of (a subset of) classic predicate logic, it lacks the ability to reason about inconsistent or incomplete information. Belief-augmented Frames (BAF) is a frame-based logic system that associates with each frame a supporting and a refuting belief value. In this paper, we propose a new ontology language Belief-augmented OWL (BOWL) by integrating OWL DL and BAF to incorporate the notion of confidence. BOWL is paraconsistent, hence it can perform useful reasoning services in the presence of inconsistencies and incompleteness. We define the abstract syntax and semantics of BOWL by extending those of OWL. We have proposed reasoning algorithms for various reasoning tasks in the BOWL framework and we have implemented the algorithms using the constraint logic programming framework. One example in the sensor fusion domain is presented to demonstrate the application of BOWL.