| Review: |
Advances in sensory technology, high performance computing and high-density storage have all produced massive complex datasets in a variety of areas in science and engineering. Data mining promises to allow the analysis of these complex datasets to extract useful information from them. This book begins with a survey of analysis problems in a number of applications, identifies common themes across these areas, and uses them to define an end-to-end process of data mining. This includes processing the raw image or mesh data to identify the object; extracting relevant features that describe the object; detecting patterns common to the objects; and displaying the patterns for validation. There are chapters on: data mining in science and engineering; common themes in mining scientific data; the scientific data mining process; reducing the size of the dataset; fusing different data modalities; enhancing image data; finding objects in the data; extracting features describing the objects; reducing the dimension of the dataset; finding patterns in the data; visualising the data and validating the results; scientific data mining systems; and lessons learned, challenges and opportunities. |