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Cross domain fusion for spatiotemporal applications: taking interdisciplinary, holistic research to the next level

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2022

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Springer

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Exploiting the power of collective use of complementing data sources for the discovery of new correlations and findings offers enormous additional value compared to the summed values of isolated analysis of the individual information sources. In this article, we will introduce the concept of “cross domain fusion” (CDF) as a machine learning and pattern mining driven and multi-disciplinary research approach for fusing data and knowledge from a variety of sources enabling the discovery of answers of the question to be examined from a more complete picture. The article will give a basic introduction in this emerging field and will highlight examples of basic CDF tasks in the field of marine science.

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Renz, Matthias; Kröger, Peer; Koschmider, Agnes; Landsiedel, Olaf; Tavares de Sousa, Nelson (2022): Cross domain fusion for spatiotemporal applications: taking interdisciplinary, holistic research to the next level. Informatik Spektrum: Vol. 45, No. 5. DOI: 10.1007/s00287-022-01489-6. Springer. PISSN: 1432-122X. pp. 271-277

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