Abstract
Classification, association rules and clustering are used in the study to improve understanding of the presence of sharks in near shore waters during tourist seasons in middle Atlantic coastal waters, specifically North Carolina. The Global Shark Attack File combined with data on environmental, biotic and meteorological factors is prepared for analysis using the CRISP-DM process. In future work, combined inputs including a standardized hashtag for twitter mining, real time weather and water information, and data on crab and turtle presence will provide real-time input to an app or a dashboard providing early warning of shark presence.
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Kaulkar, S., Vinodh, L., Thompson, P. (2018). Initial Analysis of Multivariate Factors for Prediction of Shark Presence and Attacks on the Coast of North Carolina. In: Ceci, M., Japkowicz, N., Liu, J., Papadopoulos, G., Raś, Z. (eds) Foundations of Intelligent Systems. ISMIS 2018. Lecture Notes in Computer Science(), vol 11177. Springer, Cham. https://doi.org/10.1007/978-3-030-01851-1_41
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