000			01627 a2200205 4500
005			20250926124828.0
008			241204b |||||||| |||| 00| 0 eng d
020			_a9783319318592
041			_aeng
082			_a005.7 _bMahD
245			_aData Science and Big Data Computing : _bFrameworks and Methodologies / _cedited by Zaigham Mahmood
260			_aSwitzerland: _bSpringer; _c©2016
300			_axxi, 319p.
520			_aThis illuminating text/reference surveys the state of the art in data science, and provides practical guidance on big data analytics. Expert perspectives are provided by authoritative researchers and practitioners from around the world, discussing research developments and emerging trends, presenting case studies on helpful frameworks and innovative methodologies, and suggesting best practices for efficient and effective data analytics. Features: reviews a framework for fast data applications, a technique for complex event processing, and agglomerative approaches for the partitioning of networks; introduces a unified approach to data modeling and management, and a distributed computing perspective on interfacing physical and cyber worlds; presents techniques for machine learning for big data, and identifying duplicate records in data repositories; examines enabling technologies and tools for data mining; proposes frameworks for data extraction, and adaptive decision making and social media analysis.
650			_aComputer Science
650			_aData Mining and Predictive Analytics
650			_aBig Data Modeling and Management
700			_aMahmood, Zaigham [Ed.]
942			_cBK
999			_c7049 _d7049