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George Mason University

1. Carvalho, Rommel Novaes. Probabilistic Ontology: Representation and Modeling Methodology .

Degree: 2011, George Mason University

The past few years have witnessed an increasingly mature body of research on the Semantic Web (SW), with new standards being developed and more complex problems being addressed. As complexity increases in SW applications, so does the need for principled means to cope with uncertainty in SW applications. Several approaches addressing uncertainty representation and reasoning in the SW have emerged. Among these is Probabilistic Web Ontology Language (PR-OWL), which provides WEB Ontology Language(OWL) constructs for representing Multi-Entity Bayesian network (MEBN) theories. However, there are several important ways in which the initial version PR-OWL 1 fails to achieve full compatibility with OWL. Furthermore, although there is an emerging literature on ontology engineering, little guidance is available on the construction of probabilistic ontologies. This research proposes a new syntax and semantics, defined as PR-OWL 2, which improves compatibility between PR-OWL and OWL in two important respects. First, PR-OWL 2 follows the approach suggested by Poole et al. to formalizing the association between random variables from probabilistic theories with the individuals, classes and properties from ontological languages such as OWL. Second, PR-OWL 2 allows values of random variables to range over OWL datatypes. To address the lack of support for probabilistic ontology engineering, this research describes a new methodology for modeling probabilistic ontologies called the Uncertainty Modeling Process for Semantic Technologies (UMP-ST). To better explain the methodology and to verify that it can be applied to different scenarios, this dissertation presents step-by-step constructions of two different probabilistic ontologies. One is used for identifying frauds in public procurements in Brazil and the other is used for identifying terrorist threats in the maritime domain. Both use cases demonstrate the advantages of PR-OWL 2 over its predecessor. Advisors/Committee Members: Laskey, Kathryn B (advisor).

Subjects/Keywords: Probabilistic Ontologies; Uncertainty Modeling Process; PR-OWL; MEBN; Methodology; Bayesian Network

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APA (6th Edition):

Carvalho, R. N. (2011). Probabilistic Ontology: Representation and Modeling Methodology . (Thesis). George Mason University. Retrieved from http://hdl.handle.net/1920/6616

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Carvalho, Rommel Novaes. “Probabilistic Ontology: Representation and Modeling Methodology .” 2011. Thesis, George Mason University. Accessed November 12, 2019. http://hdl.handle.net/1920/6616.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Carvalho, Rommel Novaes. “Probabilistic Ontology: Representation and Modeling Methodology .” 2011. Web. 12 Nov 2019.

Vancouver:

Carvalho RN. Probabilistic Ontology: Representation and Modeling Methodology . [Internet] [Thesis]. George Mason University; 2011. [cited 2019 Nov 12]. Available from: http://hdl.handle.net/1920/6616.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Carvalho RN. Probabilistic Ontology: Representation and Modeling Methodology . [Thesis]. George Mason University; 2011. Available from: http://hdl.handle.net/1920/6616

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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