Berry M.J.A. – Data Mining Techniques For Marketing, Sales & Customer Relationship Management

unsupervised learning, 57

non-time series data, 246

untruthful learning sources, 44–48

SQL data, 572–573

UPC (uniform product code), 555

statistics, 128–129

UPS, transaction processing

training sets

systems, 3–4

coverage of values, 232

up-selling

MBR (memory-based reasoning),

customer relationships, 467

TEAMFLY

263–264

marketing campaigns, 111, 115–116

model sets, partitioning, 71

U.S. Census Bureau Web site, 94

optimization as, 230

usage stimulation marketing

uses for, 52

campaigns, 111

transaction data, OLAP, 476–477

user roles, data transformation, 58–60

transaction processing systems,

customer relationship

V

management, 3–4

validation

transactional records, 574

assumptions, 67

transactors, behavior-based

neural networks, 218

variables, 580

validation sets

transfer function, neural

model sets, partitioning, 71

networks, 223

test sets, partitioning, 71

TRANS_MASTER file, customer

uses for, 52

signatures, 559

value added-services, predication

traveling salesman problem, graph

tasks, 10

theory, 327–329

valued outcomes, estimation, 9

trends, capturing, 75

values

triangle inequality, distance

comparing with descriptions, 65

function, 272

with meaning, data correction, 74

trivial rules, association rules, 297

missing, 590–591

truncated data, statistics, 162

Team-Fly®

470643 bindex.qxd 3/8/04 11:08 AM Page 643

Index 643

variables

Web servers

data selection, 63–64

cookies, 109

variable selection problems, neural

transaction processing systems, 3

networks, 233

Web sites

variance

customer response to marketing

analysis of, 124

campaigns, tracking, 109

defined, 81

RuleQuest, 190

neural networks, 199

U.S. Census Bureau, 94

reduction in, splits, decision trees, 183

weight columns, 548

standard deviation and, 138

weighted graphs, graph theory,

statistics, 138

322, 324

variations, percent, 105

weighted voting, 281–282

vectors, angles between, 361–362

weighting, automatic cluster

vendor credibility, 537

detection, 363–365

virtual items, association rules, 307

welcome periods, loyalty

virtuous cycle

programs, 518

action tasks, 30

well-defined distance, distance

business opportunities, identifying,

function, 271

27–28

winback approach, customer

data transformation, 28–30

relationships, 470

discussed, 28

wireless communications industries

results, measuring, 30–32

business opportunities, identifying,

stages of, 26

34–35

visualization tools, data exploration, 65

MOU (minutes of use), 38

voice node, fax machines, 341

rate plans, finding appropriate, 7

voice recognition, free text

women, differential response analysis

resources, 556

and, 107

voluntary churn, 118–119, 521

word-of-mouth advertising, 283

voting

positive ratings, 284

Z

weighted, 281–282

zip codes

as categorical value, 239

W

distance function, 276–277

warehouses, searching data in, 61–62

zone boundaries, adjusting, using

warranty claims data, useful data

automatic cluster detection, 380

sources, 60

z-scores, 551

web crawlers, spiders, 331

z-values, statistics, 131, 138

Web pages

classification, 9

useful data sources, 60

Pages: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154

Leave a Reply 0

Your email address will not be published. Required fields are marked *