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Knowledge Engineering: a Learning and Application Guide (250,00 руб.)

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Первый авторGavrilova T. A.
АвторыZhukova S. V., Graduate School of Management SPbSU
ИздательствоСПб.: Высшая школа менеджмента
Страниц133
ID304209
АннотацияKnowledge Engineering is the discipline of mapping intellectual assets. Through this guide, students are introduced to the major practical issues of knowledge engineering techniques. Developing business information structuring skills are the key to successful knowledge representation and sharing in any organisation. Students are trained to use Mind Manager and CMap software in order to support understanding of highly multidisciplinary horizons of knowledge engineering. Applications of recent advances in information processing and cognitive science to management problems are introduced in a variety of interrelated exercises designed to form an e-portfolio. The design of an e-portfolio makes it possible to reveal the tradeoffs of visual knowledge modelling, invent and evaluate different alternative methods and solutions for better understanding, representation, sharing and transfer of knowledge.
Кому рекомендованоThe guide is written to support “Knowledge Engineering” delivered to students of the “Master of International Management” graduate program.
УДК005:004
ББК65.290-2
Gavrilova, T.A. Knowledge Engineering: a Learning and Application Guide [Электронный ресурс] / S.V. Zhukova, Graduate School of Management SPbSU, T.A. Gavrilova .— СПб. : Высшая школа менеджмента, 2012 .— 133 с. — Текст на англ. яз. — Режим доступа: https://rucont.ru/efd/304209

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St. Petersburg State University Graduate School of Management T.A. Gavrilova, S.V. Zhukova KNOWLEDGE ENGINEERING: a learning and application guide St. Petersburg 2012 Reviewers: Professor A.G. Medvedev, Doctor of Economics, Graduate School of Management SPbSU Professor A.V. Smirnov Doctor of Science, deputy director of SPII RAS Published in accordance with requirements of Curriculum Design and Development Committee, Graduate School of Management SPbSU Gavrilova T.A., Zhukova S.V. Knowledge Engineering: learning and application guide / T. A. Gavrilova, S. V. Zhukova; Graduate School of Management SPbSU. — SPb.: Publishing Centre “Graduate School of Management”, 2012. — p. 133. <...> Developing business information structuring skills are the key to successful knowledge representation and sharing in any organisation. <...> Applications of recent advances in information processing and cognitive science to management problems are introduced in a variety of interrelated exercises designed to form an e-portfolio. <...> The design of an e-portfolio makes it possible to reveal the tradeoffs of visual knowledge modelling, invent and evaluate different alternative methods and solutions for better understanding, representation, sharing and transfer of knowledge. <...> The guide is written to support “Knowledge Engineering” delivered to students of the “Master of International Management” graduate program. © Graduate School of Management SPbSU, 2012 Contents PREFACE. 5 INTRODUCTION .7 CHAPTER 1. <...> EPORTFOLIO DEVELOPMENT.36 4.3 PREPARING FOR A FINAL EXAM.40 APPENDIX A. COMPUTER SCIENCE HISTORY FACTS. 41 APPENDIX B. ORCHESTRATING ONTOLOGIES. 51 APPENDIX C. BUSINESS ENTERPRISE ONTOLOGIES. 75 APPENDIX D. INFORMATION MAPPING SOFTWARE. 91 APPENDIX E. COURSE SYLLABUS “KNOWLEDGE ENGINEERING”. 95 APPENDIX F. AN EXAMPLE OF AN EPORTFOLIO. 105 CONCLUSION. 128 REFERENCES . 129 Preface This guide is intended to support students in understanding the basics of knowledge engineering and structuring in order to apply intelligent technologies to various subject domains (business, social, economic, educational, humanities, etc.). <...> The course’s goals are focused on using the results of multidisciplinary research in knowledge engineering, data structuring and cognitive science in information processing and modern management. <...> Special software (mind mapping and concept mapping) makes it possible <...>
Knowledge_Engineering_Learning_and_Application_Guide.pdf
Reviewers: Professor A.G. Medvedev, Doctor of Economics, Graduate School of Management SPbSU Professor A.V. Smirnov Doctor of Science, deputy director of SPII RAS Published in accordance with requirements of Curriculum Design and Development Committee, Graduate School of Management SPbSU Gavrilova T.A., Zhukova S.V. Knowledge Engineering: learning and application guide / T. A. Gavrilova, S. V. Zhukova; Graduate School of Management SPbSU. — SPb.: Publishing Centre “Graduate School of Management”, 2012. — p. 133. Knowledge Engineering is the discipline of mapping intellectual assets. Through this guide, students are introduced to the major practical issues of knowledge engineering techniques. Developing business information structuring skills are the key to successful knowledge representation and sharing in any organisation. Students are trained to use Mind Manager and CMap software in order to support understanding of highly multidisciplinary horizons of knowledge engineering. Applications of recent advances in information processing and cognitive science to management problems are introduced in a variety of interrelated exercises designed to form an e-portfolio. The design of an e-portfolio makes it possible to reveal the tradeoffs of visual knowledge modelling, invent and evaluate different alternative methods and solutions for better understanding, representation, sharing and transfer of knowledge. The guide is written to support “Knowledge Engineering” delivered to students of the “Master of International Management” graduate program. © Graduate School of Management SPbSU, 2012
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Contents PREFACE............................................................................................................................. 5 INTRODUCTION ..................................................................................................................7 CHAPTER 1. CONCEPTUAL MODELLING ...............................................................................8 1.1. INTENSIONAL AND EXTENSIONAL DEFINITIONS .............................................................................8 1.2. MINDMAPS .........................................................................................................................9 1.3. CONCEPT MAPS ..................................................................................................................11 1.4. FRAMES ............................................................................................................................13 CHAPTER 2. DECISION MODELLING ................................................................................... 14 2.1. DECISION TABLES ................................................................................................................14 2.2. DECISION TREE ...................................................................................................................16 2.3. CAUSE AND EFFECT DIAGRAM ...............................................................................................20 2.4. FLOWCHARTS.....................................................................................................................21 2.5. CAUSAL CHAINS ..................................................................................................................25 2.6. FUZZY KNOWLEDGE .............................................................................................................27 2.7. КNOWLEDGE ELICITATION AND STRUCTURING ...........................................................................28 CHAPTER 3. REPRESENTING KNOWLEDGE WITH ONTOLOGIES........................................... 30 3.1. TYPES OF ONTOLOGIES .........................................................................................................32 3.2. ONTOLOGICAL ENGINEERING.................................................................................................34 CHAPTER 4. SELF‐TRAINING IN KNOWLEDGE ENGINEERING............................................... 35 4.1. ROADMAP OF IN‐CLASS ASSIGNMENTS.....................................................................................35 4.2. E‐PORTFOLIO DEVELOPMENT.................................................................................................36 4.3 PREPARING FOR A FINAL EXAM................................................................................................40 APPENDIX A. COMPUTER SCIENCE HISTORY FACTS............................................................ 41 APPENDIX B. ORCHESTRATING ONTOLOGIES..................................................................... 51 APPENDIX C. BUSINESS ENTERPRISE ONTOLOGIES............................................................. 75 APPENDIX D. INFORMATION MAPPING SOFTWARE........................................................... 91 APPENDIX E. COURSE SYLLABUS “KNOWLEDGE ENGINEERING”......................................... 95 APPENDIX F. AN EXAMPLE OF AN E‐PORTFOLIO.............................................................. 105 CONCLUSION.................................................................................................................. 128 REFERENCES ................................................................................................................... 129
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