Abstract
The traditional research paradigm in the sciences was hypothesis-driven. Over the last decade or so, this hypothesis-driven view has been replaced with a data-driven view of scientific research. In almost all fields of scientific endeavor, large research teams are systematically collecting data on questions of great import. Knowledge and insights are gained through data analysis and mining, feeding this inversion of science, i.e., rather than going from hypothesis to data, we use data to generate and validate hypotheses and to generate knowledge and understanding. The same can be said for applications in the commercial realm.
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Zaki, M.J. (2012). A Journey in Pattern Mining. In: Gaber, M. (eds) Journeys to Data Mining. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28047-4_16
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