Special issue on data mining applications and case study

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Journal Article
Neurocomputing, 2012, 92 pp. 1 - 2
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Recent years have witnessed an increasing number of applications featuring machine learning and data mining techniques; examples include genetic classification of diseases in bioinformatics, behavioralcultural modeling in social science, risk management in economic and financial markets, and many others. The main driving force behind the trend is the data rich, knowledge poor reality and vast requirement to make sense out of data, which essentially places the algorithms from prototypes into application systems, and moves the research from labs to the real world. While machine learning and data mining research has advanced significantly in recent years, especially in academia, traditional emphasis has been on the development of new theories, data structures, algorithms, and frameworks with the objective of advancing the underlying technical solutions. Very few dedicated research forum are available to discuss the root of the researchapplications.
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