NDLI: Modeling a probabilistic ontology for Maritime Domain Awareness

Content Provider	IEEE Xplore Digital Library
Author	Carvalho, R.N. Haberlin, R. Costa, P.C.G. Laskey, K.B. Chang, K.C.
Copyright Year	2011
Description	Author affiliation: Center of Excellence in C4I / The Sensor Fusion Lab, George Mason University, MS 4B5, Fairfax, VA 22030-4444 U.S.A. (Carvalho, R.N.; Haberlin, R.; Costa, P.C.G.; Laskey, K.B.; Chang, K.C.)
Abstract	Situational awareness and prediction are essential elements of information fusion. Both involve various types of uncertainty and require a sound automated inferential process. Probabilistic ontologies support uncertainty management in se-mantically aware systems, and facilitate modular, interoperable systems. This paper describes the process of developing a probabilistic ontology for a Maritime Domain Awareness application. The ontology was created to support identification of ships behaving suspiciously enough to be declared ships of interest. The original model was expanded in two ways: to provide reasons for declaring a ship as being of interest, and to include individual crew member associations. The latter is achieved by supporting inferences about a person's close relations, group associations, communications, and background influences to assess his likelihood of having terrorist links.
Starting Page	1
Ending Page	8
File Size	820015
Page Count	8
File Format	PDF
ISBN	9781457702679
e-ISBN	9780982443828
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-07-05
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Intl Society of Info Fusion
Subject Keyword	Marine vehicles Terrorism Probabilistic logic Ontologies Uncertainty Organizations Electronic countermeasures PR-OWL modeling methodology probabilistic ontology uncertainty reasoning predictive situational awareness web services Bayesian networks MEBN
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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PROGNOS: Predictive situational awareness with probabilistic ontologies

A multi-disciplinary approach to high level fusion in predictive situational awareness

Scalable uncertainty treatment using triplestores and the OWL 2 RL profile

Pr-owl 2 case study: a maritime domain probabilistic ontology.

A First-Order Bayesian Tool for Probabilistic Ontologies (2008)

Ontology based context modeling and reasoning using OWL

A probabilistic extension to ontology language OWL

Uncertainty reasoning for service-based situational awareness information on the Semantic Web

An enhanced spatial reasoning ontology for maritime anomaly detection

Modeling a probabilistic ontology for Maritime Domain Awareness

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PROGNOS: Predictive situational awareness with probabilistic ontologies

A multi-disciplinary approach to high level fusion in predictive situational awareness

Scalable uncertainty treatment using triplestores and the OWL 2 RL profile

Pr-owl 2 case study: a maritime domain probabilistic ontology.

A First-Order Bayesian Tool for Probabilistic Ontologies (2008)

Ontology based context modeling and reasoning using OWL

A probabilistic extension to ontology language OWL

Uncertainty reasoning for service-based situational awareness information on the Semantic Web

An enhanced spatial reasoning ontology for maritime anomaly detection

Modeling a probabilistic ontology for Maritime Domain Awareness