NDLI: Coupled Heterogeneous Association Rule Mining (CHARM): Application Toward Inference of Modulatory Climate Relationships

Content Provider	IEEE Xplore Digital Library
Author	Ii, D.L.G. Pendse, S.V. Padmanabhan, K. Angus, M.P. Tetteh, I.K. Srinivas, S. Villanes, A. Semazzi, F. Kumar, V. Samatova, N.F.
Copyright Year	2013
Description	Author affiliation: Univ. of Minnesota, Minneapolis, MN, USA (Kumar, V.) \|\| North Carolina State Univ., Raleigh, NC, USA (Ii, D.L.G.; Pendse, S.V.; Padmanabhan, K.; Angus, M.P.; Tetteh, I.K.; Srinivas, S.; Villanes, A.; Semazzi, F.; Samatova, N.F.)
Abstract	The complex dynamic climate system often exhibits hierarchical modularity of its organization and function. Scientists have spent decades trying to discover and understand the driving mechanisms behind western African Sahel summer rainfall variability, mostly via hypothesis-driven and/or first-principles based research. Their work has furthered theory regarding the connections between various climate patterns, but the key relationships are still not fully understood. We present Coupled Heterogeneous Association Rule Mining (CHARM), a computationally efficient methodology that mines higher-order relationships between these subsystems' anomalous temporal phases with respect to their effect on the system's response. We apply this to climate science data, aiming to infer putative pathways/cascades of modulating events and the modulating signs that collectively define the network of pathways for the rainfall anomaly in the Sahel. Experimental results are consistent with fundamental theories of phenomena in climate science, especially physical processes that best describe sub-regional climate.
Sponsorship	Toshiba
Starting Page	1055
Ending Page	1060
File Size	953421
Page Count	6
File Format	PDF
ISBN	9780769551081
ISSN	15504786
DOI	10.1109/ICDM.2013.142
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Meteorology Couplings Itemsets Measurement Data mining Oceans Manganese knowledge discovery association rules climate data coupling
Content Type	Text
Resource Type	Article

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