Archaeoinformatics - Data Science

MA: Extending Expressiveness of Meta-Structures in Heterogeneous Information Network

Contact: Christian Beth, M.Sc.

Heterogeneous information networks (HINs) are graphs, where nodes have different types, and edges form different relations between the nodes, and thus allow semantically rich modelling of virtually any kind of data and information, ranging from protein-protein interaction networks to bibliogrpahical networks. The meta-path is a composite relationship between nodes in an HIN that is an integral part of state-of-the-art similarity/relevance measures in HINs, which are an integral part for downstream data mining tasks such as clustering, classification, or link prediction in HINs. To allow for more powerful, complex, and expressive relationships, the meta-structure was developed. It felxibly combines meta-path relations with the 'and'-linkage, which allows the user to specify more precisely what she is looking for. But why stop at the 'and'-linkage? Why not consider 'or', 'not', or other logical constraints? In this thesis you will design and study effective (meaningful) and efficient (fast, scalable) relevance measures based on more expressive meta-structures.