AI201 | Knowledge Representation & Reasoning
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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 programIn 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).
|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|