This course focuses on how techniques from semantic Artificial Intelligence (AI) can provide a technological foundation for enabling Knowledge Management (KM) tasks and processes. Semantic Artificial Intelligence denotes an emerging family of technologies which currently enjoy large-scale up-take in the industry. After a broad introduction of AI techniques for KM, the course will focus on semantic based AI techniques. Firstly, it will cover the basics of how (expert) knowledge can be captured in information artifacts such as taxonomies, ontologies and knowledge graphs. Secondly, the course will introduce methods to build such information artifacts from implicit knowledge (from employees) and explicit knowledge residing in data and documents in an enterprise. Thirdly, the course will also cover topics related to storing and querying such novel knowledge structures.

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 the doctor's note.  

40% Exam

40% Individual/Group Assignment (dependant on number of participants)

20% End-term presentation of the assignment

Grading scale:

<60% (5)

60% - 69% (4)

70% - 79% (3)

80% - 89% (2)

90% - 100% (1)