Order metrics for semantic knowledge systems

Authors:
Cliff Joslyn;Emilie Hogan
Affiliations:
National Security Directorate, Pacific Northwest National Laboratory, Seattle, Washington;Mathematics Department, Rutgers University
Venue:
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part II
Year:
2010

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Abstract

Knowledge systems technologies, as derived from AI methods and used in the modern Semantic Web movement, are dominated by graphical knowledge structures such as ontologies and semantic graph databases A critical but typically overlooked aspect of all of these structures is their admission to analyses in terms of formal hierarchical relations The partial order representations of whatever hierarchy is present within a knowledge structure afford opportunities to exploit these hierarchical constraints to facilitate a variety of tasks, including ontology analysis and alignment, visual layout, and anomaly detection We introduce the basic concepts of order metrics and address the impact of a hierarchical (order-theoretical) analysis on knowledge systems tasks.