Knowledge Analysis & Management
We will go through text analysis techniques such as part of speech tagging, dependency parsing, text summarization, sentiment analysis, and we will consider knowledge query and representation technologies, such as SPARQL, RDF and OWL.
Knowledge extraction and representation are key enablers for data comprehension and decision making. This course will cover techniques for the extraction of knowledge from natural language documents and for the representation of knowledge as ontologies and semantic webs.
Students will be involved in practical exercises and will experiment with the presented techniques by applying them to the course projects.
Optional written mid-term exam; final oral exam; optional homework; two mandatory projects.
- Master of Science in Artificial Intelligence, Lecture, Elective, 2nd year
- Master of Science in Artificial Intelligence, Lecture, Elective, 1st year
- Master of Science in Software & Data Engineering, Lecture, 2nd year
- PhD programme of the Faculty of Informatics, Lecture, Elective, 1st year (4 ECTS)