TY - GEN
T1 - CAREY
T2 - 10th Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems, OTM 2011: EI2N+NSF ICE 2011, ICSP+INBAST 2011, ISDE 2011, ORM 2011, OTMA 2011, SWWS+MONET+SeDeS 2011, and VADER 2011
AU - Acosta, Maribel
AU - Goncalves, Marlene
AU - Vidal, Maria Esther
PY - 2011
Y1 - 2011
N2 - Nowadays, climate changes are impacting life on Earth; ecological effects as warming of sea-surface temperatures, catastrophic events as storms or mudslides, and the increase of infectious diseases, are affecting life and development. Unfortunately, experts predict that global temperatures will increase even more during the next years; thus, to decide how to assist possibly affected people, experts require tools that help them to discover potential risky regions based on their weather conditions. We address this problem and propose a tool able to support experts in the discovery of these risky areas. We present CAREY, a federated tool built on top of a weather database, that implements a semi-supervised data mining approach to discover regions with similar weather observations which may characterize micro-climate zones. Additionally, Top-k Skyline techniques have been developed to rank micro-climate areas according to how close they are to a given weather condition of risk. We conducted an initial experimental study as a proof-of-concepts, and the preliminary results suggest that CAREY may provide an effective support for the visualization of potential risky areas.
AB - Nowadays, climate changes are impacting life on Earth; ecological effects as warming of sea-surface temperatures, catastrophic events as storms or mudslides, and the increase of infectious diseases, are affecting life and development. Unfortunately, experts predict that global temperatures will increase even more during the next years; thus, to decide how to assist possibly affected people, experts require tools that help them to discover potential risky regions based on their weather conditions. We address this problem and propose a tool able to support experts in the discovery of these risky areas. We present CAREY, a federated tool built on top of a weather database, that implements a semi-supervised data mining approach to discover regions with similar weather observations which may characterize micro-climate zones. Additionally, Top-k Skyline techniques have been developed to rank micro-climate areas according to how close they are to a given weather condition of risk. We conducted an initial experimental study as a proof-of-concepts, and the preliminary results suggest that CAREY may provide an effective support for the visualization of potential risky areas.
UR - http://www.scopus.com/inward/record.url?scp=81255166894&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-25126-9_61
DO - 10.1007/978-3-642-25126-9_61
M3 - Conference contribution
AN - SCOPUS:81255166894
SN - 9783642251252
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 494
EP - 503
BT - On the Move to Meaningful Internet Systems, OTM 2011 Workshops - Confederated Int. Workshops and Posters
Y2 - 17 October 2011 through 21 October 2011
ER -
