Titlebook: Big Data Analysis: New Algorithms for a New Society; Nathalie Japkowicz,Jerzy Stefanowski Book 2016 Springer International Publishing Swit

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Data Mining in Finance: Current Advances and Future Challenges,as the Velocity (in terms of speed of arrival) and the Variety, in terms of the various types of data collected. This chapter focuses on techniques that address these issues. Specifically, we turn our attention to the financial sector, which has become paramount to business. Our discussion centers o

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Discovering Networks of Interdependent Features in High-Dimensional Problems,nt features and rule networks do not only reflect some syntactical properties of the data and classifiers but also may convey meaningful clues about true interactions in the modeled biological system. In this chapter we develop further our method of Monte Carlo Feature Selection and Interdependency

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Big Data Analysis: New Algorithms for a New Society

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J. Gasco,J. Sendra,J. Lim,I. Ngs within a spectrum of problems related to concept drift. Finally, we discuss some promising research directions from the application perspective, and present recommendations for application driven concept drift research and development.

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An Overview of Concept Drift Applications,s within a spectrum of problems related to concept drift. Finally, we discuss some promising research directions from the application perspective, and present recommendations for application driven concept drift research and development.

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Big Data and the Internet of Things,mprove” their performance over time. Big data analytics has been identified as a key enabler for the IoT. In this chapter, we discuss various avenues of the IoT where big data analytics either is already making a significant impact or is on the cusp of doing so. We also discuss social implications and areas of concern.

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Book 2016ea. ..It demonstrates that Big Data Analysis opens up new research problems which were either never considered before, or were only considered within a limited range. In addition to providing methodological discussions on the principles of mining Big Data and the difference between traditional stati