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476 Part Three Key System Applications for the Digital Age
Key Terms
3-D printing, 459 Intelligent agents, 473
Agent-based modeling, 473 Intelligent techniques, 454
Artificial intelligence (AI), 463 Investment workstations, 462
Augmented reality (AR), 462 Knowledge, 450
Backward chaining, 465 Knowledge base, 463
Case-based reasoning (CBR), 466 Knowledge discovery, 463
Communities of practice (COPs), 453 Knowledge management, 451
Computer-aided design (CAD), 459 Knowledge network systems, 456
Data, 449 Knowledge work systems (KWS), 454
Digital asset management systems, 456 Learning management system (LMS), 457
Enterprise content management systems, 455 Machine learning, 468
Enterprise-wide knowledge management systems, 453 Neural networks, 468
Expert systems, 463 Organizational learning, 451
Explicit knowledge, 450 Social bookmarking, 456
Folksonomies, 456 Structured knowledge, 455
Forward chaining, 465 Tacit knowledge, 450
Fuzzy logic, 467 Taxonomy, 456
Genetic algorithms, 472 Virtual Reality Modeling Language (VRML), 462
Hybrid AI systems, 474 Virtual reality systems, 459
Inference engine, 465 Wisdom, 450
Review Questions
1. What is the role of knowledge management and 3. What are the major types of knowledge work sys-
knowledge management programs in business? tems and how do they provide value for firms?
• Define knowledge management and explain • Define knowledge work systems and describe
its value to businesses. the generic requirements of knowledge work
• Describe the important dimensions of knowl- systems.
edge. • Describe how the following systems support
• Distinguish between data, knowledge, and knowledge work: CAD, virtual reality, aug-
wisdom and between tacit knowledge and mented reality, and investment workstations.
explicit knowledge. 4. What are the business benefits of using intelli-
• Describe the stages in the knowledge manage- gent techniques for knowledge management?
ment value chain. • Define an expert system, describe how it
2. What types of systems are used for enterprise- works, and explain its value to business.
wide knowledge management and how do they • Define case-based reasoning and explain how
provide value for businesses? it differs from an expert system.
• Define and describe the various types of • Define machine learning and give some exam-
enterprise-wide knowledge management sys- ples.
tems and explain how they provide value for • Define a neural network, and describe how it
businesses. works and how it benefits businesses.
• Describe the role of the following in facilitat- • Define and describe fuzzy logic, genetic algo-
ing knowledge management: portals, wikis, rithms, and intelligent agents. Explain how
social bookmarking, and learning manage- each works and the kinds of problems for
ment systems. which each is suited.
MIS_13_Ch_11 Global.indd 476 1/17/2013 2:30:07 PM
