0658 Applications of Semantic AI in Knowledge Management
Dr. Fajar Juang Ekaputra
Contact details
Weekly hours
Language of instruction
09/05/23 to 11/19/23
Registration via LPIS
Notes to the course
Day Date Time Room
Tuesday 12/05/23 08:00 AM - 11:00 AM TC.4.17
Thursday 12/07/23 09:00 AM - 12:00 PM D5.1.003
Friday 12/15/23 09:00 AM - 12:00 PM TC.4.15
Tuesday 12/19/23 09:00 AM - 12:00 PM TC.3.07
Friday 01/12/24 09:00 AM - 12:00 PM TC.4.15
Thursday 01/18/24 09:00 AM - 12:00 PM TC.4.15
Thursday 01/25/24 09:00 AM - 01:30 PM TC.4.15

This course focuses on the capabilities, methods and techniques of Semantic Artificial Intelligence (AI) and their applications to support Knowledge Management (KM) tasks and systems. Semantic AI denotes an emerging family of Semantic Web technologies that enjoy large-scale up-take in the industry. 

Firstly, it will cover the general description of Semantic AI capabilities relevant to the KM tasks and systems. Secondly, the course will cover applications, methods and techniques of Semantic AI in real-world use cases, which include: 

  • Value proposition of Semantic AI
  • Semantic AI for Knowledge Exploration
  • Semantic AI for Information Extraction
  • Semantic AI for System Transparency
  • Recent Trends of Semantic AI Research and Applications
Learning outcomes

This course enables the participants to learn and apply semantic AI methods and tools in Knowledge Management. After successful completion of the course, students will be able to: 

  • Explain the key terms and value propositions of Semantic AI for Knowledge Management.
  • Understand the concepts, apply methods, and utilise tools from Semantic AI on selected tasks and applications for Knowledge Management.
  • Provide insights into the recent trends in Semantic AI and its application in academic and industrial applications.

Furthermore, students will get familiar with the recent research developments in this field.

Attendance requirements

Attendance is mandatory, with at least 80% of the hours attended, as per WU requirements regarding PI courses. The absences can be compensated in cases of illness with a doctor's note.  

Teaching/learning method(s)

This course builds on lectures, discussions, hands-on exercises, quizzes, assignments and student presentations.

Teaching methods will include:

  • Research-based teaching relying on the latest research advances in the area
  • Practical experience on selected Semantic AI methods and tools
  • Invited talks from companies that base their business models on semantic technologies


  • 20% quizzes
  • 40% group assignment (including presentation)
  • 40% exam


  • <60% (5)
  • 60% - 69% (4)
  • 70% - 79% (3)
  • 80% - 89% (2)
  • 90% - 100% (1)
Prerequisites for participation and waiting lists

Positive completion of courses 1 and 2 of the “Knowledge Management” SBWL. 


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Recommended previous knowledge and skills

Participants are expected to be familiar with basic Semantic Web technologies concepts and standards, such as ontologies, RDF/S, OWL, and SPARQL. 

Availability of lecturer(s)

via Email

Last edited: 2023-10-09