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OBJECTIVES

OBJECTIVES. Why do businesses today need knowledge management programs and systems for knowledge management? Which information system applications are most useful for distributing, creating, and sharing knowledge in the firm?

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OBJECTIVES

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  1. OBJECTIVES • Why do businesses today need knowledge management programs and systems for knowledge management? • Which information system applications are most useful for distributing, creating, and sharing knowledge in the firm? • What are the business benefits of using artificial intelligence technology for knowledge management? • How can businesses use expert systems and case-based reasoning to capture knowledge? • How can organizations benefit from using neural networks and other intelligent techniques? Managing Knowledge

  2. MANAGEMENT CHALLENGES • Designing knowledge systems that genuinely enhance organizational performance • Identifying and implementing appropriate organizational applications for artificial intelligence Managing Knowledge

  3. Creation of new standard operating procedures and business processes reflecting experience Set of processes Creates, gathers, stores, maintains, and disseminates knowledge Organizational Learningand Knowledge Management Managing Knowledge

  4. Systems and Infrastructure for Knowledge Management • Tacit Knowledge • Expertise and experience not formally documented • Best Practices • Successful solutions or problem-solving methods developed by specific organization or industry • Organizational Memory • Stored learning from organization’s history • Used for decision making and other purposes Managing Knowledge

  5. Knowledge management requires an IT infrastructure that facilitates the collection and sharing of knowledge as well as software for distributing information and make it more meaningful Managing Knowledge

  6. INFORMATION ANDKNOWLEDGE WORK SYSTEMS • Distributing Knowledge: Office and Document Management Systems • Typical Office Systems • Knowledge Work Systems (KWS) • Changes in the construction management process • Requirements of knowledge work systems • Examples of Knowledge Work Systems • Sharing Knowledge: Group Collaboration Systems and Enterprise Knowledge Environments Managing Knowledge

  7. Office Systems • Manage and coordinate work of data and knowledge workers • Connect work of local information workers with all levels and functions of organization • Connect organization to external world • Example: Word processing, voice mail, and imaging Document imaging systems • Convert documents and images into digital form • Can be stored and accessed by the computer Knowledge repository • Documented knowledge in a single location Managing Knowledge

  8. The three major roles of offices Managing Knowledge

  9. Components of an imaging system Managing Knowledge

  10. Web publishing & document management Managing Knowledge

  11. Creating Knowledge:Knowledge Work Systems • Aid knowledge workers in creation and integration of new knowledge • Specialized tools for specific types of knowledge work • User-friendly interface Managing Knowledge

  12. Changes in the construction project management process Managing Knowledge

  13. Requirements of knowledge work systems Managing Knowledge

  14. Examples of Knowledge Work Systems • Computer-aided design (CAD) • Virtual reality systems • Virtual Reality Modeling Language (VRML) • Investment workstations Managing Knowledge

  15. Sharing Knowledge: Group Collaboration Systems and Enterprise Knowledge Environments • Groupware • Intranets and Enterprise Knowledge Environments • Enterprise information portals • Teamware Managing Knowledge

  16. Requirements of knowledge work systems Managing Knowledge

  17. Artificial Intelligence (AI) • What is Artificial Intelligence? • Effort to develop computer-based systems that behave as humans • Includes natural language, robotics, perceptive systems, expert systems, and intelligent machines • Why Business is Interested in Artificial Intelligence • Stores information in active form • Creates mechanism not subjected to human feelings • Eliminates routine and unsatisfying jobs • Enhances organization’s knowledge base • Generates solution to specific problems Managing Knowledge

  18. The AI Family Managing Knowledge

  19. Capturing Knowledge: Expert Systems • Knowledge Base • Rule-based Expert System • Rule Base • Knowledge Frames • AI shell • Inference Engine • Forward Chaining • Backward Chaining Managing Knowledge

  20. Rules in an AI program Managing Knowledge

  21. Inference engines in expert systems Managing Knowledge

  22. Organizational Intelligence:Case-Based Reasoning • Captures and stores collective knowledge • Represents knowledge as database of cases and solutions Managing Knowledge

  23. A neural network uses rules it “learns” from patterns in data to construct a hidden layer of logic Managing Knowledge

  24. Intelligent agent technology at work Managing Knowledge

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