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022			_a1862-5355
024	7		_a10.1007/11634.1862-5355 _2doi
210	1	0	_aAdv Data Anal Classif
245	1	0	_aAdvances in Data Analysis and Classification _h[electronic resource] : _bTheory, Methods, and Applications in Data Science / _cedited by Maurizio Vichi, Andrea Cerioli, Hans A. Kestler, Akinori Okada, Claus Weihs.
264		1	_aBerlin/Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer.
300			_bonline resource.
520			_aThe international journal Advances in Data Analysis and Classification (ADAC) is designed as a forum for high standard publications on research and applications concerning the extraction of knowable aspects from whatever types of data. It publishes articles on topics as, e.g., Structural, quantitative, or statistical approaches for the analysis of data, Advances in classification, clustering, and pattern recognition methods, Strategies for modeling complex data and mining large data sets, Methods for the extraction of knowledge from whatever type of data, and Applications of advanced methods in specific domains of practice. In particular, this comprises the consideration and handling of new data types as well as the analysis of complex structures such as text data and webfiles. Whereas the discussion of theoretical, statistical, or algorithmic advances in methodology is a major issue (e.g., in classification and clustering), the journal encourages strongly the publication of applications that illustrate how new domain-specific knowledge can be made available from data by skillful use of data analysis methods. In addition to contributed papers on specific topics, the journal also publishes survey papers that outline, and illuminate, the basic ideas and techniques of special approaches. On occasion, specialized topics will be presented in a special issue. The journal is supported by several scientific societies which aim to foster the area of classification and data analysis. Supported by the International Federation of Classification Societies Funded by the Italian, German, and Japanese Classification Societies (CLADAG, GfKl, JCS) Officially cited as: Adv Data Anal Classif.
650		0	_aStatistics .
650		0	_aStatistics .
650		0	_aBiometry.
650		0	_aStatistics .
650		0	_aSocial sciences—Statistical methods.
650		0	_aData mining.
650	1	4	_aStatistical Theory and Methods.
650	2	4	_aStatistics in Business, Management, Economics, Finance, Insurance.
650	2	4	_aBiostatistics.
650	2	4	_aStatistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
650	2	4	_aStatistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy.
650	2	4	_aData Mining and Knowledge Discovery.
700	1		_aVichi, Maurizio. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aCerioli, Andrea. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aKestler, Hans A. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aOkada, Akinori. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aWeihs, Claus. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt
710	2		_aSpringerLink (Online service)
776	0	8	_iPrinted version: _x1862-5347
856	4	0	_uhttps://doi.org/10.1007/11634.1862-5355 _zHybrid
999			_c4766 _d4766