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.
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Joslyn, C., Hogan, E. (2010). Order Metrics for Semantic Knowledge Systems. In: Corchado, E., Graña Romay, M., Manhaes Savio, A. (eds) Hybrid Artificial Intelligence Systems. HAIS 2010. Lecture Notes in Computer Science(), vol 6077. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13803-4_50
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DOI: https://doi.org/10.1007/978-3-642-13803-4_50
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