Chapter 11Managing Knowledge

Dimensions of Knowledge

Knowledge Management – business processes developed in an organization/create, store, transfer, apply knowledge Acquisition Storage Dissemination Application

Communities of practice (COP) – informal social networks/ people with similar work related interests and activities

Terms

Manage knowledge in your organization

Enterprise-wide (general purpose; collect, store, distribute, and apply digital content and knowledge)

Knowledge work systems (specialized systems; engineers, scientists, etc; discovering and creating new knowledge)

Intelligent Techniques (data mining, expert systems, neural networks, fuzzy logic, etc.)

Knowledge Management Systems (KMS)

Types of knowledge Structured (explicit and formal) Semistructured (email, chat rooms, etc) Unstructured (in head – tacit)

Enterprise content management systems Hold all three types of knowledge 80 percent of organization’s knowledge is

semistructured or unstructured Can help create a classification scheme (taxonomy)

Enterprise-wide KMS

Digital asset management systems (work with digital objects)

Knowledge network systems (expertise location and management system; hold information from experts in the firm)

Collaboration tools and learning management systems (LMS) (tools for various types of learning and training) Social bookmarking Folksonomies

Enterprise-wide (cont)

Knowledge workers (create knowledge for organization) Knowledge work systems (specialized systems for

knowledge workers) Sufficient computing power Require links to external knowledge bases Give the worker quick and easy access to databases Workstations optimized for specific tasks performedTypes: Computer aided design (CAD) Virtual reality

Programs for web Use VRML Augmented Reality

Knowledge Work Systems

For Tacit knowledge Expert systems Case-based reasoning Fuzzy logic

For Knowledge discovery Neural Networks Data Mining

Artificial Intelligence (computer-based/attempt to emulate human behavior) Power of AIPeople Power App

Intelligent Techniques

Expert Systems (tacit knowledge/specific and limited domain of human expertise) Knowledge base (rules) Inference engine (search)

Forward chaining (Info entered by user; searches rule base for conclusion)

Backward chaining (starts with hypothesis; try to confirm or disprove)

Case based reasoning (CBR) (past experiences of human specialists/organizational knowledge/stored in database/look for similar parameters)

Intelligent Techniques (cont)

Fuzzy Logic (rule based/approximate or subjective values/for imprecise info)

Neural networks (look for patterns and relationships in data)

Genetic algorithms (finding optimal solution/based on evolutionary biology techniques)

Hybrid AI systems (integrate genetic algorithms, fuzzy logic, neural networks, expert systems)

Intelligent agents (software programs/work in background/carry out tasks for user) Agent-based modeling (model behavior of humans)

Intelligent Techniques (cont)