Инженерия знаний

Knowledge Engineering 

Инженерия знаний

 

Instructor:

Tatiana Gavrilova, PhD, DSc, Professor, Head of Department of Information Technologies in Management, Graduate School of Management, St Petersburg University

Workload:

6,0 ECTS

Contact hours: 45 

Prerequisites:

no

Goals and objectives:

This course introduces students to the practical application of intelligent technologies into the different subject domains (business, social, economical, educational, human, etc.). It will give students insight and experience in key issues of data and knowledge processing in companies. In class and discussion sections, students will be able to discuss issues and tradeoffs in visual knowledge modeling, and invent and evaluate different alternative methods and solutions to better knowledge representation and understanding, sharing and transfer. Lecture course’ goals are focused at using the results of multidisciplinary research in knowledge engineering, data structuring and cognitive sciences into information processing and modern management. The handon practice will be targeted at e-doodling with Mind Manager and Cmap software tools.  

Course Content:

The course features the knowledge engineering as the practical methodology of data and knowledge processing. Knowledge engineering will be defined as a set of techniques to manage big amounts of personal and corporate information. The stress will be put at visual methods as mind mapping and concept-mapping.

The course examines a number of related topics, such as: 
• system analysis and its applications;
• the relationship among, and roles of, data, information, and knowledge in different applications including marketing and management, and the varying approaches needed to ensure their effective implementation and deployment; 
• knowledge acquisition and structuring including the principles and visual methods; 
• defining and identifying of cognitive aspects for knowledge modeling and visual representation; 

• e-doodling with Visio, Mindjet and Cmap software tools.  

Teaching Methods:

The class will feature lectures, discussions, short tests and, students will have several hand-on practices using mind-mapping and concept mapping software. Lectures will be important but the emphasis will be on learning through training, games, discussions and short tests. A good deal of the course will focus on auto-reflection and auto-formalizing of knowledge, training of analytical and communicative abilities, discovery, creativity, achieving new perspectives, synthesizing evidence from disparate sources, and gaining new insights in this fascinating new field.  

Course Reading:

Required Reading: 
• Okada A., Shum B. S., Sherborne T. (Eds) Knowledge Cartography: Software Tools and Mapping Techniques (Advanced Information and Knowledge Processing). Springer, 2008. 
• Gavrilova T., Zhukova S. Knowledge Engineering. Learning guide, GSOM, 2013. 
Optional Reading : 
• Nast J. Idea Mapping: How to Access Your Hidden Brain Power, Learn Faster, Remember More, and Achieve Success in Business. Wiley, 2006.
• Schuster P.M. Concept Mapping: A Critical-Thinking Approach to Care Planning, F. A. Davis Company, 2007. 
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