Response-guided community detection: Application to climate index discovery

Gonzalo A. Bello, Michael Angus, Navya Pedemane, Jitendra K. Harlalka, Fredrick H.M. Semazzi, Vipin Kumar, Nagiza F. Samatova

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

Discovering climate indices–time series that summarize spatiotemporal climate patterns–is a key task in the climate science domain. In this work, we approach this task as a problem of response-guided community detection; that is, identifying communities in a graph associated with a response variable of interest. To this end, we propose a general strategy for response-guided community detection that explicitly incorporates information of the response variable during the community detection process, and introduce a graph representation of spatiotemporal data that leverages information from multiple variables. We apply our proposed methodology to the discovery of climate indices associated with seasonal rainfall variability. Our results suggest that our methodology is able to capture the underlying patterns known to be associated with the response variable of interest and to improve its predictability compared to existing methodologies for data-driven climate index discovery and official forecasts.

Original languageEnglish (US)
Title of host publicationMachine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2015
EditorsVitor Santos Costa, Carlos Soares, Annalisa Appice, Annalisa Appice, Pedro Pereira Rodrigues, Vitor Santos Costa, Carlos Soares, João Gama, Alípio Jorge, Pedro Pereira Rodrigues, João Gama, Vitor Santos Costa, Alípio Jorge, Annalisa Appice, Pedro Pereira Rodrigues, João Gama, Annalisa Appice, Carlos Soares, Alípio Jorge, João Gama, Pedro Pereira Rodrigues, Vitor Santos Costa, Carlos Soares, Alípio Jorge
PublisherSpringer Verlag
Pages736-751
Number of pages16
ISBN (Print)9783319235240, 9783319235240, 9783319235240, 9783319235240
DOIs
StatePublished - 2015
EventEuropean Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2015 - Porto, Portugal
Duration: Sep 7 2015Sep 11 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9285
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherEuropean Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2015
CountryPortugal
CityPorto
Period9/7/159/11/15

Bibliographical note

Funding Information:
This material is based upon work supported in part by the Laboratory for Analytic Sciences, the U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research, and NSF grant 1029711.

Publisher Copyright:
© Springer International Publishing Switzerland 2015.

Keywords

  • Climate index discovery
  • Community detection
  • Seasonal rainfall prediction
  • Spatiotemporal data

Fingerprint Dive into the research topics of 'Response-guided community detection: Application to climate index discovery'. Together they form a unique fingerprint.

Cite this