AI201 | Knowledge Representation & Reasoning
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Course overview

Knowledge representation and reasoning is the study concerning approaches and methods for representing knowledge and algorithms and techniques to manipulate such a symbolic representation to infer new knowledge from existing one. This field has received a lot of attention in recent years due to the emergence of Semantic Web, which has become a fertile ground for research and application of knowledge representation and reasoning. The central idea behind Semantic Web is to enhance data on the World Wide Web by so-called metadata, which describes the meaning (semantics) of the data. This enhancement is made possible by formal knowledge representation languages, which makes the data processable and understandable by machines.

What you will learn
  • CLO-1 Understand theoretical and practical issues in symbolic knowledge representation and reasoning, in general. (C2 - Understanding).

  • CLO-2 Understand the capabilities of specific knowledge representation formalisms for specific tasks. (C2 - Understanding).

  • CLO-3 Make effective use of techniques specific to specific knowledge representation problems and formalisms. (C3 - Applying).

  • CLO-4 Make effective use of special-purpose languages for reasoning, ontologies, planning, reasoning about actions, constraint programming. (C4 - Analyzing).

Structured Web
Documents in XML, DTD, XML Schema, Namespaces, XPath Expressions, XQuery FLWOR, XQuery Examples and Tutorial
Semantic Web
Importance of Meaning, Understanding Content on the Web, Semantic Web Technology and Web of Data, How to name things? URI
Knowledge Representation
RDF and Turtle Serialization, Model Building with RDFs, Query RDF Based Knowledge Base
Ontologies and Logic
Ontologies Basics and Types, Web Ontology Language OWL , Knowledge Representation with Ontologies, The Foundation of Logic, Model-Theoretic Semantics
Logic and Reasoning
Prepositional Logic, Tableau Algorithms, First Order Logic, Description Logic, ALC Attribute Language with ALC
Ontology Engineering
OWL Classes, Properties, and Individuals, OWL Class Hierarchies and Disjunctiveness, OWL Property Relationships, Rules
Course program
In this course we cover in depth such knowledge representation languages for expressing metadata, called ontology languages. We will cover the Resource Description Framework (RDF) and the Web Ontology Language (OWL), both of which are recommended standards by the World Wide Web Consortium (W3C).
Lessons Name Description Duration Week Slides
1 Introduction From Web 1.0 to Web 3.0, Semantic Web Beginning 1 hours 1 KRRS2200
2 Structured Web Documents in XML 2 hours 1 KRRS2201
3 Structure XML Documents DTD, SML Schema, Namespaces 3 hours 2 KRRS2202
4 Access XML Documents XPath, XQuery 3 hours 3 KRRS2203
5 Semantic Web Importance of Meaning, Web of Data, DBPedia 3 hours 4 KRRS2204
6 Resource Description Framework URIs, RDF and Turtle Serialization 3 hours 5 KRRS2205
7 RDF Based Knowledge Representation RDF Reification, Model Building with RDFs 6 hours 6,7 KRRS2206
8 SPARQL - Query Language for RDF DBPedia Knowledge Graph, SPARQL Queries, Open Link Virtuoso 6 hours 8,9 KRRS2207
9 Ontology Representation Ontology in Philosophy and Computer Science, Ontology Types 3 hours 10 KRRS2208
10 Propositional Logic Foundation of Logic, Model-Theoretic Semantics 3 hours 11 KRRS2209