000			02118cam a2200325 a 4500
001			15581039
003			KPTM
005			20150318034005.0
008			090109s2009 paua b 001 0 eng
010			_a2008056149
020			_a9780898716757
040			_cKPTM
050	0	0	_aQA76.9.D343 _bK151 2009
084			_aST 530 _2rvk
100	1		_aKamath, Chandrika.
245	1	0	_aScientific data mining : _ba practical perspective / _cChandrika Kamath.
260			_aPhiladelphia : _bSociety for Industrial and Applied Mathematics, _cc2009.
300			_axviii, 286 p. : _bill. ; _c26 cm.
504			_aIncludes bibliographical references (p. 235-277) and index.
505	0		_aData 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.
520	8		_aChandrika 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.
650		0	_aData mining.
650		0	_aScience _xDatabases
650		0	_aEngineering _xDatabases.
856	4	1	_3Table of contents only _uhttp://www.loc.gov/catdir/enhancements/fy0916/2008056149-t.html
856	4	2	_3Publisher description _uhttp://www.loc.gov/catdir/enhancements/fy0916/2008056149-d.html
856	4	2	_3Contributor biographical information _uhttp://www.loc.gov/catdir/enhancements/fy0916/2008056149-b.html
856	4	1	_3Table of contents _uhttp://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=017363421&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
942			_2lcc _cBK
999			_c3149 _d3149