Abstract
Data Mining has become a buzzword in industry in recent years. It is something that everyone is talking about but few seem to understand. There are two reasons for this lack of understanding: First is the fact that Data Mining researchers have very diverse backgrounds such as machine learning, psychology and statistics. This means that the research is often based on different methodologies and communication links e.g. notation is often unique to a particular research area which hampers the exchange of ideas and the dissemination to the wider public. The second reason for the lack of understanding is that the main ideas behind Data Mining are often completely opposite to mainstream statistics and as many companies interested in Data Mining already employ statisticians, such a change of view can create opposition.
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Jessen, H.C., Paliouras, G. (2001). Data Mining in Economics, Finance, and Marketing. In: Paliouras, G., Karkaletsis, V., Spyropoulos, C.D. (eds) Machine Learning and Its Applications. ACAI 1999. Lecture Notes in Computer Science(), vol 2049. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44673-7_18
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DOI: https://doi.org/10.1007/3-540-44673-7_18
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