LEADER 00847nam2-22003011i-450- 001 990000383660403321 005 20001010 035 $a000038366 035 $aFED01000038366 035 $a(Aleph)000038366FED01 035 $a000038366 100 $a20001010d--------km-y0itay50------ba 101 0 $aita 105 $ay-------001yy 200 1 $aJahrbuch der Chemie. Band 11$fRichard Meyer. 210 $aBraunschweig$cverlag von Vieweg & Sohn$d1892-1920 215 $a28 voll., ill., 24 cm 461 0$1001000028602$12001$aJahrbuch der Chemie 676 $a540 700 1$aMeyer,$bRichard$0334223 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990000383660403321 952 $a04 060-61/11$bOPV CI 01648$fDINCH 959 $aDINCH 996 $aJahrbuch der Chemie. Band 11$9135969 997 $aUNINA DB $aING01 LEADER 05655nam 2200769 450 001 9910140289803321 005 20200520144314.0 010 $a1-118-41674-0 010 $a1-118-43426-9 010 $a1-118-42022-5 035 $a(CKB)2670000000523076 035 $a(EBL)1629158 035 $a(SSID)ssj0001112227 035 $a(PQKBManifestationID)11661572 035 $a(PQKBTitleCode)TC0001112227 035 $a(PQKBWorkID)11158787 035 $a(PQKB)10414951 035 $a(DLC) 2013043850 035 $a(Au-PeEL)EBL1629158 035 $a(CaPaEBR)ebr10837603 035 $a(CaONFJC)MIL573941 035 $a(OCoLC)870586961 035 $a(CaSebORM)9781118416747 035 $a(MiAaPQ)EBC1629158 035 $a(EXLCZ)992670000000523076 100 $a20131031h20142014 uy| 0 101 0 $aeng 135 $aurunu||||| 181 $ctxt 182 $cc 183 $acr 200 10$aHeuristics in analytics $ea practical perspective of what influences our analytical world /$fCarlos Andre Reis Pinheiro, Fiona McNeill 205 $a1st edition 210 1$aHoboken, New Jersey :$cJohn Wiley & Sons, Inc.,$d[2014] 210 4$dİ2014 215 $a1 online resource (254 p.) 225 1 $aWiley & SAS business series 300 $aDescription based upon print version of record. 311 $a1-118-34760-9 320 $aIncludes bibliographical references and index. 327 $aHeuristics in Analytics: A Practical Perspective of What Influences Our Analytical World; Copyright; Contents; Preface; Acknowledgments; About the Authors; Chapter 1: Introduction; The Monty Hall Problem; Evolving Analytics; The Business Relevance of Analytics; The Role of Analytics in Innovation; Innovation in a Changing World; Summary; Chapter 2: Unplanned Events, Heuristics, and the Randomness in Our World; Heuristics Concepts; Heuristics in Operations; The Butterfly Effect; Random Walks; The Drunkard's Walk; Probability and Chance; Summary 327 $aChapter 3: The Heuristic Approach and Why We Use It Heuristics in Computing; Heuristic Problem-Solving Methods; Genetic Algorithms: A Formal Heuristic Approach; Foundation of Genetic Algorithms; Initialization; Selection; Reproduction; Termination; Pseudo-Code Algorithm; Benefits of Genetic Algorithms; Influences in Competitive Industries; Genetic Algorithms Solving Business Problems; Summary; Chapter 4: The Analytical Approach; Introduction to Analytical Modeling; The Competitive-Intelligence Cycle; Data; Information; Knowledge; Intelligence; Experience; Summary 327 $aChapter 5: Knowledge Applications That Solve Business Problems Customer Behavior Segmentation; Collection Models; Insolvency Segmentation; Collection Notice Recovery; Anticipating Revenue from Collection Actions; Insolvency Prevention; Bad-Debt Classification; Avoiding Taxes; Fraud-Propensity Models; New Fraud Detection; Classifying Fraudulent Usage Behavior; Summary; Chapter 6: The Graph Analysis Approach; Introduction to Graph Analysis; Graphs Structures, Network Metrics, and Analyses Approaches; Network Metrics; Types of Subgraphs; Summary; Chapter 7: Graph Analysis Case Studies 327 $aCase Study: Identifying Influencers in Telecommunications Background in Churn and Sales; Internal Networks; Customer Influence; Customer Influence and Business Event Correlation; Possible Business Applications and Final Figures in Churn and Sales; Case Study: Claim Validity Detection in Motor Insurance; Background in Insurance and Claims; Network Definition; Participant Networks; Group Analysis; Identifying Outliers; Final Figures in Claims; Visualizing for More Insight; Final Figures in Insurance Exaggeration; Case Study: Fraud Identification in Mobile Operations 327 $aBackground in Telecommunications Fraud Social Networks and Fraud; Community Detection; Finding the Outliers within Communities; Rules and Thresholds for Community Outliers; Fraudster Visualization; Final Figures in Fraud; Summary; Chapter 8: Text Analytics; Text Analytics in the Competitive-Intelligence Cycle; Information Revisited; Knowledge Revisited; Linguistic Models; Text-Mining Models; Intelligence Revisited; Experience Revisited; Summary; Bibliography; Index 330 $aA practical guide to deploying mathematical and statistical models when performing analytics The Heuristics in Analytics describes analytic processes and how they fit into the heuristic world around us. In spite of the strong heuristic characteristics of the analytical processes, this important book emphasizes the need to have the proper tools to engage analytics. It describes the analytical process from the exploratory analysis in respect to business scenarios and corporate environments, to model developments; and from statistics, probability, stochastic, mathematics, and arti 410 0$aWiley and SAS business series. 606 $aManagement$xStatistical methods 606 $aDecision making$xStatistical methods 606 $aBusiness planning$xStatistical methods 606 $aHeuristic algorithms 606 $aSystem analysis 615 0$aManagement$xStatistical methods. 615 0$aDecision making$xStatistical methods. 615 0$aBusiness planning$xStatistical methods. 615 0$aHeuristic algorithms. 615 0$aSystem analysis. 676 $a658.4/033 700 $aReis Pinheiro$b Carlos Andre$f1940-$0880217 701 $aMcNeill$b Fiona$0880218 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910140289803321 996 $aHeuristics in analytics$91965349 997 $aUNINA