ñòð. 129 |

information brokers, supermarket

considerations, 51

chains as, 15â€“16

decision-making process, 50â€“51

information gain, entropy, 178â€“180

generating, 51

information technology, data

market basket analysis, 51

transformation, 58â€“60

null hypothesis, statistics and,

as products, 14

125â€“126

recommendation-based businesses,

I 16â€“17

IBM, relational database management Inmon, Bill (Building the Data

software, 13

Warehouse), 474

ID and key variables, 554

input columns, 547

ID3 (Iteractive Dichotomiser 3), 190

input layer, free-forward neural

identification

networks, 226

columns, 548

input variables, target fields, 37

customer signatures, 560â€“562

inputs/outputs, neural networks, 215

good prospects, 88â€“89

insourcing data mining, 524â€“525

problem management, 43

insurance claims, classification, 9

proof-of-concept projects, 599â€“601

interactive systems, response times, 33

identified versus anonymous Internet resources

transactions, association rules, 308

customer response to marketing

identity distance, distance function, 271

campaigns, tracking, 109

ignored columns, 547

RuleQuest, 190

images, binary data, 557

U.S. Census Bureau, 94

imperfections, in data, 34

interval variables, 549, 552

implementation

interviews

neural networks, 212

business opportunities,

proof-of-concept projects, 601â€“605

identifying, 27

implicit parallelism, 438

proof-of-concept projects, 600

in-between relationships, customer

intrinsic information, splits, decision

relationships, 453

trees, 180

income, house-hold level data, 96

introduction, of products, 27

630 Index

intuition, data exploration, 65

case study, 343â€“346

involuntary churn, 118â€“119, 521

classification, 9

item popularity, market based

discussed, 321

analysis, 293

fax machines, 337â€“341

item sets, market based analysis, 289

graphs

Iterative Dichotomiser 3 (ID3), 190

acyclic graphs, 331

communities of interest, 346

K cyclic, 330â€“331

key and ID variables, 554

data as, 340

KDD (knowledge discovery in

directed graphs, 330

databases), 8

edges, 322

Kimball, Ralph (The Data Warehouse

graph-coloring algorithm, 340â€“341

Toolkit), 474

Hamiltonian path, 328

Kleinberg algorithm, link analysis,

nodes, 322

332â€“333

planar graphs, 323

K-means clustering, 354â€“358

traveling salesman problem,

knowledge discovery in databases

327â€“329

(KDD), 8

vertices, 322

Kolmogorov-Smirnov (KS) tests, 101

hubs, 332â€“334

Kleinberg algorithm, 332â€“333

L root sets, 333

large-business relationships, customer

search programs, 331

relationship management, 3â€“4

stemming, 333

leaf nodes, classification, 167

weighted graphs, 322, 324

learning

linkage graphs, 77

opportunities, customer interactions,

lists, ordered and unordered, 239

520â€“521

literature, market research, 22

supervised, 57

logarithms, data transformation, 74

training techniques as, 231

logical schema, OLAP, 478

truthful sources, 48â€“50

logistic methods, box diagrams, 200

unsupervised, 57

long form, census data, 94

untruthful sources, 44â€“48

long-term trends, 75

life stages, customer relationships,

lookup tables, auxiliary information,

455â€“456

570â€“571

lifetime customer value, customer

loyalty

relationships, 32

customers, 520

lift ratio

loyalty programs

comparing models using, 81â€“82

marketing campaigns, 111

lift charts, 82, 84

welcome periods, 518

problems with, 83

luminosity, 351

linear processes, 55

M

linear regression, 139

link analysis

mailings

authorities, 333â€“334

marketing campaigns, 97

candidates, 333

non-response models, 35

Index 631

as statistical analysis

marginal customers, 553

acuity of testing, 147â€“148

market based analysis

confidence intervals, 146

differentiation, 289

proportion, standard error of,

discussed, 287

139â€“141

geographic attributes, 293

results, comparing, using confiÂ

item popularity, 293

dence bounds, 141â€“143

item sets, 289

sample sizes, 145

market basket data, 51, 289â€“291

targeted acquisition campaigns, 31

marketing interventions, tracking,

types of, 111

293â€“294

up-selling, 115â€“116

order characteristics, 292

usage stimulation, 111

products, clustering by usage,

ñòð. 129 |