LEADER 04132nam 22007095 450 001 9910298980103321 005 20200630075607.0 010 $a1-4471-6407-5 024 7 $a10.1007/978-1-4471-6407-4 035 $a(CKB)3710000000094950 035 $a(EBL)1697679 035 $a(OCoLC)881165892 035 $a(SSID)ssj0001186546 035 $a(PQKBManifestationID)11626287 035 $a(PQKBTitleCode)TC0001186546 035 $a(PQKBWorkID)11218035 035 $a(PQKB)10753141 035 $a(MiAaPQ)EBC1697679 035 $a(DE-He213)978-1-4471-6407-4 035 $a(PPN)177825111 035 $a(EXLCZ)993710000000094950 100 $a20140327d2014 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aMathematical Tools for Data Mining $eSet Theory, Partial Orders, Combinatorics /$fby Dan A. Simovici, Chabane Djeraba 205 $a2nd ed. 2014. 210 1$aLondon :$cSpringer London :$cImprint: Springer,$d2014. 215 $a1 online resource (834 p.) 225 1 $aAdvanced Information and Knowledge Processing,$x1610-3947 300 $aDescription based upon print version of record. 311 $a1-4471-6406-7 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aSets, Relations and Functions -- Partially Ordered Sets -- Combinatorics -- Topologies and Measures -- Linear Spaces -- Norms and Inner Products -- Spectral Properties of Matrices -- Metric Spaces Topologies and Measures -- Convex Sets and Convex Functions -- Graphs and Matrices -- Lattices and Boolean Algebras -- Applications to Databases and Data Mining -- Frequent Item Sets and Association Rules -- Special Metrics -- Dimensions of Metric Spaces -- Clustering. 330 $aData mining essentially relies on several mathematical disciplines, many of which are presented in this second edition of this book.  Topics include partially ordered sets, combinatorics,  general topology, metric spaces, linear spaces, graph theory.  To motivate the reader a significant number of applications of these mathematical tools are included ranging from association rules, clustering algorithms, classification, data constraints, logical data analysis, etc.  The book is intended as a reference for researchers and graduate students.  The current edition is a significant expansion of the first edition.  We strived to make the book self-contained, and only a general knowledge of mathematics is required.  More than 700 exercises are included and they form an integral part of the material.  Many exercises are in reality supplemental material and their solutions are included. 410 0$aAdvanced Information and Knowledge Processing,$x1610-3947 606 $aData mining 606 $aComputer science?Mathematics 606 $aComputer mathematics 606 $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030 606 $aMathematics of Computing$3https://scigraph.springernature.com/ontologies/product-market-codes/I17001 606 $aDiscrete Mathematics in Computer Science$3https://scigraph.springernature.com/ontologies/product-market-codes/I17028 606 $aComputational Mathematics and Numerical Analysis$3https://scigraph.springernature.com/ontologies/product-market-codes/M1400X 615 0$aData mining. 615 0$aComputer science?Mathematics. 615 0$aComputer mathematics. 615 14$aData Mining and Knowledge Discovery. 615 24$aMathematics of Computing. 615 24$aDiscrete Mathematics in Computer Science. 615 24$aComputational Mathematics and Numerical Analysis. 676 $a006.312 700 $aSimovici$b Dan A$4aut$4http://id.loc.gov/vocabulary/relators/aut$0771375 702 $aDjeraba$b Chabane$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910298980103321 996 $aMathematical Tools for Data Mining$92281727 997 $aUNINA