Due to advances in information technology and high performance computing, very large data sets are becoming available in many scientific disciplines. The rate of production of such data far outstrips our ability to analyze them manually. For example, a computational simulation can generate tera-bytes of data within a few hours, whereas human analysts may take several weeks to analyze these data sets. Other examples include several digital sky surveys, and data sets from the fields of medical imaging, bioinformatics, and remote sensing. As a result, there is an increasing interest in various scientific communities to explore the use of emerging data mining techniques for the analysis of these large data sets.
- Data Mining for Scientific and Engineering Applications, Tutorial at SC2001, November 12, 2001 by R.Grossman, C.Kamath and V.Kumar
- Ch 1: Introduction
- Ch 2: Classification & Regression
- Ch 3: Clustering
- Ch 4: Association Rules
- Ch 5: General Case Studies: Applying Data Mining to Scientific Data
- Ch 6: Specific Case Study: Studying for Bent-double Galaxies
- Ch 7: Preparing Scientific and Engineering Data for Mining
- Ch 8: Case Studies in Earth Science Data
- Ch 9: Case Studies in Scientific Simulation Data
- Ch 10: Data Mining Systems
- References
