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Issue No.02 - March-April (2012 vol.16)
pp: 26-34
Cory Henson , Kno.e.sis, Wright State University
Amit Sheth , Kno.e.sis, Wright State University
Krishnaprasad Thirunarayan , Kno.e.sis, Wright State University
ABSTRACT
<p>An abstraction is a representation of an environment derived from sensor observation data. Generating an abstraction requires inferring explanations from an incomplete set of observations (often from the Web) and updating these explanations on the basis of new information. This process must be fast and efficient. The authors' approach overcomes these challenges to systematically derive abstractions from observations. The approach models perception through the integration of an abductive logic framework called Parsimonious Covering Theory with Semantic Web technologies. The authors demonstrate this approach's utility and scalability through use cases in the healthcare and weather domains.</p>
INDEX TERMS
abstraction, context, sensor, observation, perception, abduction, Semantic Web, OWL
CITATION
Cory Henson, Amit Sheth, Krishnaprasad Thirunarayan, "Semantic Perception: Converting Sensory Observations to Abstractions", IEEE Internet Computing, vol.16, no. 2, pp. 26-34, March-April 2012, doi:10.1109/MIC.2012.20
REFERENCES
1. J. McCarthy, "Notes on Formalizing Context," Proc. 13th Int'l Joint Conf. Artificial Intelligence (IJCAI 93), vol. 1, Morgan Kaufmann, 1993, pp. 555–560.
2. R. Guha, Contexts: A Formalization and Some Applications, doctoral dissertation, Dept. of Computer Science, Stanford University, 1991.
3. J.A. Reggia and Y. Peng, "Modeling Diagnostic Reasoning: A Summary of Parsimonious Covering Theory," Proc. Ann. Symp. Computer Application in Medical Care, vol. 25, IEEE Press, 1986, pp. 17–29.
4. P. Murray, "Just Months after Jeopardy!, Watson Wows Doctors with Medical Knowledge,"6 June 2011; http://bit.lyk-Watson.
5. C. Henson et al., "Representation of Parsimonious Covering Theory in OWL-DL," Proc. 8th Int'l Workshop OWL: Experiences and Directions (OWLED 11), CEUR-WS.org, 2011; www.knoesis.org/libraryresource.php?id=1546 .
6. A. Sheth, C. Henson, and S.S. Sahoo, "Semantic Sensor Web," IEEE Internet Computing, vol. 12, no. 4, 2008, pp. 78–83.
7. L. Lefort et al., eds., Semantic Sensor Network XG Final Report, W3C Incubator Group Report, June 2011; www.w3.org/2005/Incubator/ssnXGR-ssn-20110628 .
8. M. Compton et al., "The SSN Ontology of the W3C Semantic Sensor Network Incubator Group," J. Web Semantics, to appear, 2012.
9. C. Elsenbroich, O. Kutz, and U. Sattler, "A Case for Abductive Reasoning over Ontologies," Proc. 3rd Int'l Workshop OWL: Experiences and Directions (OWLED 06), CEUR-WS.org, 2011; http://ceur-ws.org/Vol-216submission_25.pdf .
10. A. Sheth, "Computing for Human Experience: Semantics-Empowered Sensors, Services, and Social Computing on the Ubiquitous Web," IEEE Internet Computing, vol. 14, no. 1, 2010, pp. 88–91.
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