Knowledge Analysis & Management
People
Course director
Assistant
Description
COURSE OBJECTIVES
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.
COURSE DESCRIPTION
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
LEARNING METHODS
Students will be involved in practical exercises and will experiment with the presented techniques by applying them to the course projects.
EXAMINATION INFORMATION
Optional written mid-term exam; final oral exam; optional homework; two mandatory projects.
RECOMMENDED COURSES
- Data Design & Modeling
- Information Modeling & Analysis
REFERENCES
Lecture slides and lecture notes, available on iCorsi
Education
- Master of Science in Software & Data Engineering, Foundation course, 2nd year
- PhD programme of the Faculty of Informatics, Elective course, Lecture, 1st year (4 ECTS)
- PhD programme of the Faculty of Informatics, Elective course, Lecture, 2nd year (4 ECTS)