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 Sathyabama Institute of Science and Technology BE CSE SCSA3012 Knowledge Management Systems Syllabus SATHYABAMA INSTITUTE OF SCIENCE AND TECHNOLOGY SCHOOL OF COMPUTING SCSA3012 KNOWLEDGE MANAGEMENT SYSTEMS L T P Credits Total Marks 3 0 0 3 100 UNIT 1 INTRODUCTION 9 Hrs. Overview of Knowledge Management: The Nature of Knowledge - Data, Information and Knowledge with Examples - Types of Knowledge-Subjective View of knowledge-Objective View of knowledge-Procedural vs. Declarative Knowledge- Tacit vs. Explicit Knowledge - General vs. Specific Knowledge - Technically vs. Contextually Specific Knowledge - Knowledge and Expertise - Types of Expertise - Codifiability and Teachability of Knowledge - Specificity of Knowledge - Reservoirs of Knowledge - Characteristics of Knowledge. UNIT 2 COMPONENTS AND TECHNOLOGIES IN KMS 9 Hrs. Major components of KMS-Categories of KMS-Technologies to Manage Knowledge-Digital Libraries- Repositories-Cognitive Psychology - Kinds of Knowledge- Expert Knowledge-Thinking and Learning in Humans -Knowledge vs. Intelligence - Knowledge Based Systems for KM :dumb search, Heuristic search . UNIT 3 KNOWLEDGE ARCHITECTURE 9 Hrs. Knowledge Management Systems Life Cycle-Challenges in KM Systems Development-Conventional Vs KM Systems Life Cycle (KMSLC)-Key Differences-Key Similarities and KMSLC Approaches - Knowledge Architecture- Knowledge Creation- Nonaka’s Model of Knowledge Creation & Transformation-Knowledge Architecture-Acquiring the KM System. UNIT 4 KMS TOOLS AND TECHNIQUES 9 Hrs. Knowledge Discovery: Systems that Create Knowledge -Knowledge Capture Systems: Systems that Preserve and Formalize Knowledge - Concept Maps, Process Modelling, RSS-Wikis-Delphi Method-Knowledge Sharing Systems- Systems that Organize and Distribute Knowledge- Ontology Development Systems-Categorization and Classification Tools - XML-Based Tools - Capturing Techniques- On-Site Observation (Action Protocol) -Brainstorming, Electronic Brainstorming - Protocol Analysis (Think-Aloud Method) - Consensus Decision Making, Repertory Grid - Nominal Group Technique (NGT) - Delphi Method - Concept Mapping - Black boarding. UNIT 5 APPLICATION AND FUTURE TRENDS 9 Hrs. Components Of A Knowledge Strategy – Case Studies - Discovering New Knowledge - Data Mining - Classical statistics & statistical pattern recognition - Induction of symbolic rules -Induction trees - Artificial Neural Networks - Supervised Learning - Back Propagation -Unsupervised Learning - Kohonen Network -The Future of Knowledge Management - Protecting Intellectual Property (IP). Max.45 Hrs. COURSE OUTCOMES On completion of the course, student will be able to CO1 - An ability to create and represent knowledge to solve a problem. CO2 - Interpret data for knowledge management systems. CO3 - Identify the various knowledge architectures. CO4 - Apply the theoretical knowledge to acquire new systems. CO5 - Use the knowledge management tools. CO6 - Develop Knowledge Management Applications. TEXT / REFERENCE BOOKS 1. Elias M. Awad, Hassan M. Ghaziri (2004). Knowledge Management. Prentice Hall. ISBN: 0-13-034820-1. 2. Ian Watson (2002). Applying Knowledge Management: Techniques for Building Corporate Memories. Morgan Kaufmann. ISBN: 1558607609. 3. Madanmohan Rao (2004). Knowledge Management Tools and Techniques: Practitioners and Experts Evaluate KM Solutions. Butterworth-Heinemann. ISBN: 0750678186. 4. Amrit Tiwana (2002). The Knowledge Management Toolkit: Orchestrating IT, Strategy, and Knowledge Platforms (2nd Edition). Prentice Hall. ISBN: 013009224X. 5. Stuart Barnes (ed) (2002). Knowledge Management Systems Theory and Practice. Thomson Learning. 6. Stuart Russell, Peter Norvig (2003). Artificial Intelligence: A Modern Approach (2nd Edition). ISBN: 0-13-790395-2. END SEMESTER EXAMINATION QUESTION PAPER PATTERN Max. Marks : 100 Exam Duration : 3 Hrs. PART A: 10 Questions of 2 marks each-No choice 20 Marks PART B: 2 Questions from each unit with internal choice, each carrying 16 marks 80 Marks   |
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