CTIT University of Twente
CTIT Connecting Project

Knowledge extraction and representation from datasets

Title: knowledge extraction and representation from datasets


In order to make full use of large datasets, data needs to be selected, structured, abstracted and represented into schemas, which we call “knowledge”. This datasets can be in various forms — text, logs, sensor signals etc. The mission of this assignment is to propose a methodology to extract knowledge from certain kinds of datasets, and represent this knowledge into formalizations.

Skills required:

1. Students on computer science, artificial intelligence or cognitive science, who are motivated to explore both scientific and engineering aspects of knowledge representation.

2. Good analytical abilities.

3. Knowledge on logic, RDF, ontology, conceptual graph, and knowledge engineering is a plus.

Level: Bachelor/Master

Contact: Jason Xinghang DAI, Jasondai.fr@gmail.com