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A Dynamic and Scalable Decision Tree Based Mining of Educational Data
Abstract
The explosive growth in the amount of data in the field of biology, education, environmental research, sensor network, stock market, weather forecasting and many more due to vast use of internet in distributed environment has generated an urgent need for new techniques and tools that can intelligently automatically transform the processed data into useful information and knowledge. Hence data mining has become a research are with increasing importance. Since continuation in collection of more data at this scale, formalizing the process of big data analysis will become paramount. Given the vast amount of data are geographically spread across the globe, this means a very large number of models is generated, which raises problems on how to generalize knowledge in order to have a global view of the phenomena across the organization. This is applicable to web-based educational data. In this chapter, the new dynamic and scalable data mining approach has been discussed with educational data.
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