BA/MA: Linked Data Compression
(BA/MA, Supervisor: Basil Ell)
In recent years, more and more structured data became available on the Web in the form of linked data, thus a large amount of data represented in RDF format became available. This makes data compression an interesting research topic, both lossless compression as well as lossy compression. In this thesis we will investigate how the data mining technique frequent subgraph mining can be applied both for lossless and lossy compression of RDF datasets.
Having attended the Semantic Web lecture is a plus but no prerequisite. However, some programming skills are expected. This thesis can be framed as a bachelor thesis or as a master thesis.