91265 - Knowledge Engineering

Learning outcomes

At the end of the course, the student knows some (semi-)automated methods for joint interpretation of data and content as sources of knowledge. The student masters the basics of knowledge extraction, engineering, and linking, making data suitable to machine querying and automated reasoning, typically on decentralized platforms such as the Web.

Course contents

Knowledge graphs and ontologies

Semantic Web standards: OWL, RDF, SPARQL

Ontology Design methodologies and ontology design patterns

Reasoning methods, neuro-symbolic reasoning

Large Language Models and Knowledge Engineering: applications and research challenges

Knowledge extraction use cases: text and music

Readings/Bibliography

Notes and slides provided by the teacher.

Hitzler, P., Gangemi, A., & Janowicz, K. (2016). Ontology Engineering with Ontology Design Patterns. Amsterdam: IOS Press.

P.A. Bonatti, S. Decker, A. Polleres, V. Presutti, Knowledge graphs: new directions for knowledge representation on the Semantic Web (dagstuhl seminar 18371). Dagstuhl Rep. 8(9), 29–111 (2019)

Aidan Hogan et. al. Knowledge graphs. ACM Computing Surveys, Vol. 54, No. 4, Article 71

Semantic Web (W3C Recommendations):

OWL 2: https://www.w3.org/TR/2012/REC-owl2-rdf-based-semantics-20121211/

RDF: https://www.w3.org/TR/2014/REC-rdf11-mt-20140225/

SPARQL: https://www.w3.org/TR/2013/REC-sparql11-query-20130321

Teaching methods

Lectures, lab practice, homework, and self-assessment quizzes.

Assessment methods

• Group project: selected from a list proposed by the teachers (with individual assessment)
  

Project: The students will apply the semantic modeling methodologies acquired and experimented during the course, for the creation of a knowledge graph starting from existing resources (database, text, etc.), reusing / extending other ontologies and where necessary applying knowledge extraction tools, entity linking, ontology alignment, etc.

Teachers will assign a project to each group and will provide the specification for its realisation. Before the assignment each group will have the possibility to express two preferences on a list of available projects. Priority will be given to students' preference if possible, it cannot be guaranteed though that they will be addressed (in case of conflicts).

Teaching tools

Slides, tools for self-assessment and, discord for asynchronous discussions and communication.

Office hours

See the website of Valentina Presutti

See the website of Andrea Giovanni Nuzzolese