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European and U.S. perspectives on the sharing and integration of weather information into ATM decisions

Published in:
ATM2011, 9th USA/Europe Air Traffic Management Research and Development Seminar, 14 June 2011.

Summary

Weather is a major source of operational air traffic delays, accounting for 25 to 70 percent of all delays dependent of the geographical region. In today's Air Traffic Management (ATM) systems, a variety of weather information is available to help tactical and strategic planners better anticipate weather events that impact airspace capacity. Regretfully, the information is not always shared amongst all the stakeholders involved or well integrated into the existing ATM environment. This paper describes the high-level concepts for an improved sharing and integration or weather information into Air Traffic Management Decisions, as well as the current state and anticipated capabilities or the underlying information Management infrastructure.
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Summary

Weather is a major source of operational air traffic delays, accounting for 25 to 70 percent of all delays dependent of the geographical region. In today's Air Traffic Management (ATM) systems, a variety of weather information is available to help tactical and strategic planners better anticipate weather events that impact...

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CompositeMatch: detecting n-ary matches in ontology alignment

Published in:
OM 2009: Proc. 4th Int. Workshop on Ontology Matching, 25 October 2009, pp. 250-251.

Summary

The field of ontology alignment still contains numerous unresolved problems, one of which is the accurate identification of composite matches. In this work, we present a context-sensitive ontology alignment algorithm, CompositeMatch, that identifies these matches, along with the typical one-to-one matches, by looking more broadly at the information that a concept's relationships confer. We show that our algorithm can identify composite matches with greater confidence than current tools.
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Summary

The field of ontology alignment still contains numerous unresolved problems, one of which is the accurate identification of composite matches. In this work, we present a context-sensitive ontology alignment algorithm, CompositeMatch, that identifies these matches, along with the typical one-to-one matches, by looking more broadly at the information that a...

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