Database integrasjon og semantisk web

Most of our topics concern methods to access and connect information from inhomogeneous data sets constructed for differing purposes, using differing models. Ontologies and Knowledge graphs are relevant concepts. Some of the topics also contain elements of machine learning, but not all of them.

For this spesialisation, please contact the research group “Analytical Solutions and Reasoning.”  Available master topics are listed here.  Some recent MSc theses:

  • Improving Access to Relevant Knowledge in Large Ontologies through Best Excerpts from Text by Martin Lam. This project addresses the problem that large domain models (Ontologies) can be hard to navigate for humans. There are methods to extract “excerpts” from ontologies that give an overview of a small part of the domain, but it is hard to say what part will be useful.  In this thesis, natural language text is analysed together with an ontology to find the most relevant parts.
  • SPARQL Extension Ranking – Collaborative filtering for OptiqueVQS-queries by Tom Fredrik Christoffersen. The starting point was a graphical user interface to compose database queries, similarly to the faceted search interfaces used in many online stores, but for graph queries. This thesis investigates methods to anticipate which filters users are most likely to add next, based on filters already selected, and a log of previous queries.
  • Frog: Functions for ontologies — An extension for the OTTR-framework by Marlen Jarholt. The starting point is OTTR, a language for domain modelling developed in our group. The thesis adds functions to the OTTR language, which requires both some theoretical work on the OTTR type system, and implementation work.
Published Oct. 5, 2023 1:51 PM - Last modified Oct. 5, 2023 1:51 PM