Scientific data mining a practical perspective - Kamath, Chandrika (Philadelphia Society for Industrial and Applied Mathematics, 2009)
Chandrika Kamath describes how techniques from the multi-disciplinary field of data mining can be used to address the modern problem of data overload in science and engineering domains. Starting with a survey of analysis problems in different applications, it identifies the common themes across these domains.
Data mining in science and engineering -- Common themes in mining scientific data -- The scientific data mining process -- Reducing the size of the data -- Fusing different data modalities -- Enhancing image data -- Finding objects in the data -- Extracting features describing the objects -- Reducing the dimension of the data -- Finding patterns in the data -- Visualizing the data and validating the results -- Scientific data mining systems -- Lessons learned, challenges, and opportunities.
Recommending faculty (E2-1143): Dr. Prospero Naval Jr. for CS 284 (Machine Learning).
Keywords: Data mining; Science -- Databases; Engineering -- Databases