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022			_a2198-5812
024	7		_a40745 _2local
210	1	0	_aAnn. Data. Sci.
245	1	0	_aAnnals of Data Science _h[electronic resource] / _cedited by Yong Shi.
264		1	_aBerlin/Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer.
300			_bonline resource.
520			_aAnnals of Data Science (AODS) publishes cutting-edge research findings, experimental results and case studies of data science. Data science can be regarded as interdisciplinary techniques, including statistics, artificial intelligence, and optimization in Big Data processing and data mining for decision making. AODS encourages contributors to not only explore the theoretical bases of data science, but also address challenging problems in data science applications, such as finance, healthcare, climate changes, etc. In addition, AODS promotes the papers in discovering knowledge from heterogeneous data in big data environment, artificial intelligent algorithm research, computing power networks as well as the digital economy problems.
650		0	_aBusiness.
650		0	_aManagement science.
650		0	_aStatistics .
650		0	_aArtificial intelligence.
650		0	_aComputer science.
650		0	_aBig data.
650		0	_aData mining.
650	1	4	_aBusiness and Management.
650	2	4	_aStatistics in Business, Management, Economics, Finance, Insurance.
650	2	4	_aArtificial Intelligence.
650	2	4	_aComputer Science.
650	2	4	_aBig Data.
650	2	4	_aData Mining and Knowledge Discovery.
700	1		_aShi, Yong. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt
710	2		_aSpringerLink (Online service)
776	0	8	_iPrinted version: _x2198-5804
856	4	0	_uhttp://link.springer.com/journal/40745 _zHybrid
999			_c3569 _d3569