TY  - BOOK
AU  - Kamath,Chandrika
TI  - Scientific data mining: a practical perspective 
SN  - 9780898716757
AV  - QA76.9.D343 K151 2009
PY  - 2009///
CY  - Philadelphia
PB  - Society for Industrial and Applied Mathematics
KW  - Data mining
KW  - Science
KW  - Databases
KW  - Engineering
N1  - Includes bibliographical references (p. 235-277) and index; 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
N2  - 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
UR  - http://www.loc.gov/catdir/enhancements/fy0916/2008056149-t.html
UR  - http://www.loc.gov/catdir/enhancements/fy0916/2008056149-d.html
UR  - http://www.loc.gov/catdir/enhancements/fy0916/2008056149-b.html
UR  - http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=017363421&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
ER  -