LEADER 04815nam 22006255 450 001 9910298965403321 005 20200701151030.0 010 $a3-319-25127-9 024 7 $a10.1007/978-3-319-25127-1 035 $a(CKB)3710000000539341 035 $a(EBL)4199269 035 $a(SSID)ssj0001597047 035 $a(PQKBManifestationID)16297908 035 $a(PQKBTitleCode)TC0001597047 035 $a(PQKBWorkID)14885342 035 $a(PQKB)11756027 035 $a(DE-He213)978-3-319-25127-1 035 $a(MiAaPQ)EBC4199269 035 $a(PPN)190881585 035 $a(EXLCZ)993710000000539341 100 $a20151215d2015 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aMathematical Problems in Data Science $eTheoretical and Practical Methods /$fby Li M. Chen, Zhixun Su, Bo Jiang 205 $a1st ed. 2015. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015. 215 $a1 online resource (219 p.) 300 $aDescription based upon print version of record. 311 $a3-319-25125-2 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aIntroduction: Data Science and BigData Computing -- Overview of Basic Methods for Data Science -- Relationship and Connectivity of Incomplete Data Collection -- Machine Learning for Data Science: Mathematical or Computational -- Images, Videos, and BigData -- Topological Data Analysis -- Monte Carlo Methods and their Applications in Big Data Analysis -- Feature Extraction via Vector Bundle Learning -- Curve Interpolation and Financial Curve Construction -- Advanced Methods in Variational Learning: Segmentation with Intensity Inhomogeneity -- An On-line Strategy of Groups Evacuation From a Convex Region in the Plane -- A New Computational Model of Bigdata. 330 $aThis book describes current problems in data science and Big Data. Key topics are data classification, Graph Cut, the Laplacian Matrix, Google Page Rank, efficient algorithms, hardness of problems, different types of big data, geometric data structures, topological data processing, and various learning methods.  For unsolved problems such as incomplete data relation and reconstruction, the book includes possible solutions and both statistical and computational methods for data analysis. Initial chapters focus on exploring the properties of incomplete data sets and partial-connectedness among data points or data sets. Discussions also cover the completion problem of Netflix matrix; machine learning method on massive data sets; image segmentation and video search. This book introduces software tools for data science and Big Data such MapReduce, Hadoop, and Spark.   This book contains three parts.  The first part explores the fundamental tools of data science. It includes basic graph theoretical methods, statistical and AI methods for massive data sets. In second part, chapters focus on the procedural treatment of data science problems including machine learning methods, mathematical image and video processing, topological data analysis, and statistical methods. The final section provides case studies on special topics in variational learning, manifold learning, business and financial data rec overy, geometric search, and computing models.  Mathematical Problems in Data Science is a valuable resource for researchers and professionals working in data science, information systems and networks.  Advanced-level students studying computer science, electrical engineering and mathematics will also find the content helpful. 606 $aComputers 606 $aComputer communication systems 606 $aComputer science?Mathematics 606 $aInformation Systems and Communication Service$3https://scigraph.springernature.com/ontologies/product-market-codes/I18008 606 $aComputer Communication Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/I13022 606 $aMathematics of Computing$3https://scigraph.springernature.com/ontologies/product-market-codes/I17001 615 0$aComputers. 615 0$aComputer communication systems. 615 0$aComputer science?Mathematics. 615 14$aInformation Systems and Communication Service. 615 24$aComputer Communication Networks. 615 24$aMathematics of Computing. 676 $a004 700 $aChen$b Li M$4aut$4http://id.loc.gov/vocabulary/relators/aut$0906133 702 $aSu$b Zhixun$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aJiang$b Bo$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910298965403321 996 $aMathematical Problems in Data Science$92510486 997 $aUNINA