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Chapter 11

Chapter 11. Managing Knowledge. Dimensions of Knowledge. Terms. Knowledge Management – business processes developed in an organization/create, store, transfer, apply knowledge Acquisition Storage Dissemination Application

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Chapter 11

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  1. Chapter 11 Managing Knowledge

  2. Dimensions of Knowledge

  3. Terms • 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

  4. Knowledge Management Systems (KMS) • 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) • IntelligentTechniques (data mining, expert systems, neural networks, fuzzy logic, etc.)

  5. Enterprise-wide 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)

  6. Enterprise-wide (cont) • 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

  7. Knowledge Work Systems • 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 performed Types: • Computer aided design (CAD) • Virtual reality • Programs for web Use VRML • Augmented Reality

  8. Intelligent Techniques 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 AI People Power App

  9. Intelligent Techniques (cont) • 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)

  10. 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)

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