Video lectures for the Masters lecture "Semantic Web Technologies WS 2015/2016"
Since January 1, 2001
The web has become an object of our daily life and the amount of information there is ever growing. Besides plain texts, multimedia such as graphics, audio or video have become a predominant part of the web's information traffic. But, how can we find useful information within this huge information space? How can we make use of the knowledge contained in those web documents?
Traditional search engines for example will reach the limits of their power, when it comes to understanding information content. The Semantic Web is an extension of the traditional web in the sense that information in the form of natural language text in the web will be complemented by its explicit semantics based on a formal knowledge representation. Thus, the meaning of information expressed in natural language can be accessed in an automated way and interpreted correctly, i.e. it can be “understood“ by machines. Semantic Web technologies enable the explicit representation of knowledge and its further processing to deduce new knowledge from implicitly hidden knowledge. Previously heterogeneous data can be mapped and combined based on common knowledge representation and schemata easily extended in a dynamic way. In this lecture, you will learn the fundamentals of Semantic Web technologies and how they are applied for knowledge representation in the Web of Data.
Lecture 1: Knowledge Engineering and the Web of Data
Lecture 2: 03.11. RDF Based Knowledge Engineering
Lecture 3: 10.11. - SPARQL
Lecture 4: 17.11. - Ontologies and Logic
Lecture 5: 24.11. Tableaux Algorithm, Description Logics, DL Reasoning Problems, OWA
Lecture 6: 01.12. - Tableaux (DL), Canonical forms, Resolution (PL/FOL), History of Ontologies
Lecture 7: 08.12. - OWL and RDF(S) Semantics Basics
Lecture 8: 15.12. - Rules, Protége, RDF(S) Semantics
Lecture 9: 05.01. - SWRL, Rules expressible in OWL
Lecture 10: 12.01 - Ontology Alignment, Ontology Evaluation, More Ontology Design Methodologies
Lecture 11: 19.01. - Linked Data Engineering, Linked Data Programming, Semantic Annotation
Lecture 12: 26.01. - Named Entity Resolution, Semantic Search, Exploratory Search
Lecture 13: 02.02. - Linked Data Analytics, Semantic Recommendations
Enroll me for this course
If you would like to enroll for this course, there are no formal prerequisites or limitations. The course is free and open for everyone
. Just register for an account on openHPI and go for the course!Enroll me now
- Gain a record of achievement by earning more than 50% of the maximum number of points from all graded assignments.
- Gain a confirmation of participation by completing at least 50% of the course material.
Find out more in the certificate guidelines.