Design principles for ontological support of Bayesian evidence management

Frontiers in Artificial Intelligence and Applications

Volumn 213, Issue , 2010, Pages 163-178

  Huhns, Michael N ^a   Valtorta, Marco G ^a   Wang, Jingsong ^a  

^a UNIVERSITY OF SOUTH CAROLINA   (United States)

Author keywords

Bayesian reasoning; causal ontology; evidence management

Indexed keywords

BAYESIAN NETWORKS; DOMAIN KNOWLEDGE;

BAYESIAN ANALYSIS; BAYESIAN EVIDENCE; BAYESIAN MODELLING; BAYESIAN REASONING; CAUSAL ONTOLOGY; DESIGN PRINCIPLES; EVIDENCE MANAGEMENT; HYPOTHESIS EXPLORATIONS; INTEGRATED SYSTEMS; ONTOLOGY'S;

ONTOLOGY;

EID: 77956021622     PISSN: 09226389     EISSN: 18798314     Source Type: Book Series    
DOI: 10.3233/978-1-60750-581-5-163     Document Type: Article

References (17)

1. John Cheng, Ray Emami, Larry Kerschberg, Eugene Santos, Jr., Qunhua Zhao, Hien Nguyen, Hua Wang, Michael Huhns, Marco Valtorta, Jiangbo Dang, Hrishikesh Goradia, Jingshan Huang, and Sharon Xi, "OmniSeer: A Cognitive Framework for User Modeling, Reuse of Prior and Tacit Knowledge, and Collaborative Knowledge Services," Proceedings of the 38th Hawaii International Conference on System Sciences, HICSS38, 2005.
2. Katherine Laskey and Suzanne Mahoney, "Network Fragments: Representing Knowledge for Constructing Probabilistic Models," in Proceeding of the Thirteenth Conference on Uncertainty in Artificial Intelligence, AAAI Press, 1997, 334-341.
3. The Protégé Ontology Editor and Knowledge Acquisition System, http://protege.stanford.edu/.
4. Resource Description Framework (RDF), http://www.w3.org/RDF/.
5. Fabio G. Cozman, "The Interchange Format for Bayesian Networks," 1998. http://www.cs.cmu.edu/~fgcozman/Research/ InterchangeFormat/
6. SPARQL Query Language for RDF, http://www.w3.org/TR/rdf-sparql-query/.
7. Marco Valtorta and Yimin Huang, "Identifiability in Causal Bayesian Networks: A Gentle Introduction," Cybernetics and Systems 39:4 (2008) 425-442.
8. Marco Valtorta, John Byrnes, and Michael Huhns, "Logical and Probabilistic Reasoning to Support Information Analysis in Uncertain Domains," Proceedings of the Third Workshop on Combining Probabilty and Logic (Progic-07), Canterbury, England, September, 2007, 5-7
9. Yimin Huang and Marco Valtorta, "Pearl's Calculus of Intervention is Complete," Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence (UAI-06), 2006, 217-224.
10. Judea Pearl, Causality: Modeling, Reasoning, and Inference, Cambridge, England: Cambridge University Press, 2000.
11. Marco G. Valtorta, Y.-G. Kim, and Jirka Vomlel, "Soft Evidential Update for Multiagent Systems," International Journal of Approximate Reasoning 29:1 (2002) 71-106.
12. Peter Pirolli and Lance Good, "Evaluation of a Computer Support Tool for Analysis of Competing Hypotheses," UIR Technical Report, Palo Alto Research Center, 2004.
13. Richards J. Heuer, Jr., Psychology of Intelligence Analysis, Center for the Study of Intelligence (at http://www.cia.gov/csi/books/19104/index.html), 1999.
14. Thomas Lukasiewicz, "Probabilistic Description Logics for the Semantic Web," INFSYS Research Report 1843-06-105, Institut Für Informationssysteme, Technische Universität Wien, March 2007.
15. Pronto-A Probabilistic Reasoner for OWL DL and Pellet, http://pellet.owldl.com/pronto.
16. Zhongli Ding and Yun Peng, "A Probabilistic Extension to Ontology Language OWL," Proc. 37th Hawaii International Conference on System Sciences, HICSS37, 2004.
17. Daphne Koller, A. Levy, and Avri Pfeffer, "P-CLASSIC: A Tractable Probabilistic Description Logic," in Proc. AAAI-97, AAAI Press, 1997, 390-397.