Index
A
Action clause, of a rule, 2 26-227
Action protocol, 182
Adair, Red, 29 2-29 3
Adaptive learning systems, 342
Affinity grouping, 359
A ge effect, 169
Aggression, 108, 262
A llen, Jim ,454
A llen, William, 430-431
Alpha Corporation, 431
Ambiguity, 106
Amble, Charles, 4 1 1-4 12
Andersen C onsulting (A ccenture), 36
Anticvbersquatting C onsum er Protection
A ct,422
Application layer, 103-105
Architects, of KM systems, 102
Arcs, 197
AREAS, 337
Aristotle, 44
Arrow, A lex, 413
Artificial intelligence, 13 1-132
Association discovery, 359
Association rules, 338-341
Asynchronous collaboration, 393, 395
Atlantic Corp.,422
Authentication/security layer, 103
Authorized access layer, 127-129
Avoidance. 108, 262
B
Bandwidth, 400-401
BA N K O R, 90-91 , 92, 94-95 , 98, 102, 105
Barker, Joel Arthur, 65
Behavioral feasibility, 94
Beliefs, 57
Bell. D aniel,44
Bennet, A lex, 29
Best Buy Co., 39
Biometrics, 129
Blackboard, 199
Blackboarding, 198-200
Boeing Aircraft, 430
Boland, R. J., 116
Boolean rule, 338
Bottom -up approach
to building learning models, 331
to improving ethical behavior, 430-431
Bounded rationality, 274
Brailsford,Tom , 454
Brain drain, 35
Brainstorming, 183
electronic, 184-185, 186, 187
brainX Digital Learning System, 458
Branches, 341
Break-even analysis, 95
Buckman, Robert, 302
Business drivers of data mining, 352 -3 54
Business intelligence (BI), 351-352
Business process reengineering (BPR), 44
Business-to-business (B 2B ),3 0 6
Business to business (Internet and
extranet). 317
Business to consum er (Internet), 31 6-317
Business transactions, 361
C
Calogero, Barry,42
Cambridge Inform ation N etwork, 388
Campaign optim ization, 368
Capturing phase of KM life cycle, 48
Case, 68, 228
Case-based reasoning (C B R ), 6 7-68, 131,
132, 2 28-2 30, 231
(B ox 2.3), 69
(Figure 4.13), 133
Cases, 188
Categorizing, 396
Certainty factor, 225
Cham pion, 2 60-261 , 308
Change, 323, 324
Change leader, 455
Chase, W. G., 72
Chat rooms, 312-3 13
Chiazza, John, 307
Chief knowledge officer, 4 52-454
Child frames, 224
Chrysler Corp., 42
Chunking, 72
Chunks, 72, 151
Churchman, C. W., 116
Circular errors, 246, 248
Circular triad, 170
Cisco Systems, 296
CitiBank London, 336
Classification, 359
Classification trees, 34 1-342
Clustering, 359
CM Holdings, Inc., 429
Code of ethics, 431
Codification, 400
See also Knowledge codification
Cognitive scien ce (psychology),
59-60 , 232
Collaboration, 41 ^ 2
versus categorization, 39 6-398
knowledge portals and, 3 92-393, 395
Collaborative agents and filtering, 103
Collaborative intelligence and filtering
layer, 129-133
Collective sequential transfer, 288-291
Columbia Laboratories, Inc., 425
Common sense, 58-59 , 68
Communication, 120
difficulties, 171
interpersonal, 232
training, 263
Competition, 35 2-35 3
Com petitive advantage, 44
Compilation, 72
Computer-supported cooperative work
(C SCW ),469
Concept mapping, 195
procedure, 196-197
semantic nets and, 197-198
Consensual approval, 330
Consensus, 183, 190
Consensus decision making, 190-191
Consistency, 125
Contamination effect, 167, 170
Content m anagement, 312
of knowledge portals, 394, 396, 397
Continuous learning, 440
Control m echanism , 200
Conversion, 106
Copyright, 417
statem ent (Figure 14.2),419
Copyright and trademark violations, 416
Copyright laws, 411, 417
473

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