Introduction to knowledge engineering

Lecturer: Prof. Tatiana Gavrilova

Aims:
- To study the practical issues and foundations of knowledge and data
engineering
- To elaborate and to assess the analytical and knowledge l engineering
skills

Content
1. Introduction to Knowledge Engineering (KE)
1.1. Artificial intelligence (AI) as a cradle of KE
1.2. History of AI: brief synopsis of evolution
1.3. Main branches of knowledge-based systems' study
1.5. Knowledge and data, knowledge representation models classification
1.7. Rule-based model, frame and semantic . networks
2. Knowledge-based  systems  (KBS) development
2.1. KBS. Definition and structure
2.2. Classification of KBS
2.3. Life cycle and methodology of rapid prototyping
2.4. Developers team and role of knowledge engineer
2.5. Knowledge engineer: psychological  and professional portrait
3. Knowledge engineering.
3.1. Structure of knowledge engineering
3.2. Theoretical aspect of knowledge elicitation (psychological, linguistic
and methodological)
3.3. Classification of practical methods of knowledge elicitation
3.4. Active and passive individual methods of knowledge elicitation
3.5. Group communicative methods of knowledge elicitation
3.6. Textological methods of knowledge elicitation
3.7. Knowledge structuring techniques: object-structured analysis
4.  Ontological Engineering
4.1. Semantic ontology design: step by step
4.2. Algorithms and tips for visual design of concept maps
4.3. Ontologies as a kernel of knowledge management

Instruction : Lectures in interactive form, practical exercises
and  tests during lecture in game format.

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I have several tests the students will overcome.
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Schedule
Mo, 5.05 8-12 Liivi 2-405
Tu, 6.05 8-12         612