000			03218nam a22004815i 4500
001			978-1-84996-044-1
003			DE-He213
005			20140220084515.0
007			cr nn 008mamaa
008			100623s2010 xxk| s |||| 0|eng d
020			_a9781849960441 _9978-1-84996-044-1
024	7		_a10.1007/978-1-84996-044-1 _2doi
050		4	_aQA76.9.D343
072		7	_aUNF _2bicssc
072		7	_aUYQE _2bicssc
072		7	_aCOM021030 _2bisacsh
082	0	4	_a006.312 _223
100	1		_aAdhikari, Animesh. _eauthor.
245	1	0	_aDeveloping Multi-Database Mining Applications _h[electronic resource] / _cby Animesh Adhikari, Pralhad Ramachandrarao, Witold Pedrycz.
264		1	_aLondon : _bSpringer London : _bImprint: Springer, _c2010.
300			_aX, 130p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aAdvanced Information and Knowledge Processing, _x1610-3947
505	0		_aAn Extended Model of Local Pattern Analysis -- Mining Multiple Large Databases -- Mining Patterns of Select Items in Multiple Databases -- Enhancing Quality of Knowledge Synthesized from Multi-database Mining -- Efficient Clustering of Databases Induced by Local Patterns -- A Framework for Developing Effective Multi-database Mining Applications.
520			_aMulti-database mining is recognized as an important and strategic area of research in data mining. The authors discuss the essential issues relating to the systematic and efficient development of multi-database mining applications, and present approaches to the development of data warehouses at different branches, demonstrating how carefully selected multi-database mining techniques contribute to successful real-world applications. In showing and quantifying how the efficiency of a multi-database mining application can be improved by processing more patterns, the book also covers other essential design aspects. These are carefully investigated and include a determination of an appropriate multi-database mining model, how to select relevant databases, choosing an appropriate pattern synthesizing technique, representing pattern space, and constructing an efficient algorithm. The authors illustrate each of these development issues either in the context of a specific problem at hand, or via some general settings. Developing Multi-Database Mining Applications will be welcomed by practitioners, researchers and students working in the area of data mining and knowledge discovery.
650		0	_aComputer science.
650		0	_aData mining.
650	1	4	_aComputer Science.
650	2	4	_aData Mining and Knowledge Discovery.
650	2	4	_aInformation Systems Applications (incl. Internet).
700	1		_aRamachandrarao, Pralhad. _eauthor.
700	1		_aPedrycz, Witold. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781849960434
830		0	_aAdvanced Information and Knowledge Processing, _x1610-3947
856	4	0	_uhttp://dx.doi.org/10.1007/978-1-84996-044-1
912			_aZDB-2-SCS
999			_c110948 _d110948