В пособии основное внимание уделено системам на основе знаний и их применению, а также инженерии знаний как средству работами со знаниями, которые должны лечь в основу интеллектуальных систем. Пособие может быть использовано не только в рамках изучаемых курсов, но и при выполнении научно-исследовательских работ. Предназначено для студентов, изучающих курсы «Инженерия знаний и управление знаниями (на английском языке)» и «Технологии разработки программного обеспечения (на английском языке)», включенные в учебные планы по программе подготовки 09.04.01_17 «Интеллектуальные системы».

Most of the focus of this guide is given to knowledge-based systems and their use, as well as to knowledge engineering as a means of working with knowledge that should form the basis of intelligent systems. This guide can be used as part of the studied courses as well as when conducting research work. This study guide is intended for students studying the courses “Knowledge engineering and knowledge management” and “Software development technologies”, which is included in the curricula for the educational program 09.04.01_17 “Intelligent systems”.

• CONTENTS
• INTRODUCTION
• PART 1. KNOWLEDGE AND ITS PRELIMINARY PREPARATION
  • Intelligence and rationality
  • Information, data and knowledge
  • Neuroinformatics and knowledge engineering
  • Classes, individuals, and properties
  • Syntax, semantics, context
  • Tasks of knowledge-based systems
  • Classification of knowledge
  • Knowledge obtaining
    • Knowledge elicitation
    • Knowledge acquisition
    • Machine elicitation of knowledge
    • Knowledge formation
• PART 2. STRUCTURIZATION. TYPES OF LOGIC. TRIPLETS
  • Concept of structurization
  • Structurization in graphic representation
  • Text structurization
  • Structurization using formal languages
    • Propositional logic
    • Languages for describing sets and relations
    • First-order logic
    • Language of description logic
  • Describing rules
  • Ontology
  • DBpedia as a tool for the machine structurization of knowledge
• PART 3. FORMALIZATION
  • Methods for formalizing knowledge
  • Resources in semantic web technologies
  • Notations in semantic web technologies
  • RDF and RDFS
  • SPARQL
  • Using the library dotNetRDF
  • OWL
    • OWL-elements for discovering inconsistencies
    • OWL-elements for obtaining new knowledge
  • Describing description logic
• PART 4. KNOWLEDGE-BASED SYSTEMS
  • Dynamic rules
  • Uncertainty
  • Components of a knowledge-based system
    • Information-measuring system
    • Formulae management component
    • Neural network management component
    • Monitoring system
    • Databases and knowledge bases management systems
    • Experience analyzer component
    • User interface
    • Automated dispatch control system
    • Experiment component
    • Search component
    • Core
  • Multi-agent organization of a knowledge-based system
• REFERENCES