Knowledge Analysis & Management
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.
Specifically, 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.
Students will be involved in practical exercises and will experiment with the presented techniques by applying them to the course projects.
Optional written midterm exam; oral final exam.
- Data Design & Modeling
- Information Modeling & Analysis
- Lecture slides and lecture notes, available on iCorsi