Archaeoinformatics - Data Science

BA: Relevance Measures in Temporal Heterogeneous Information Networks

Author: Fabian Krüger

Supervisors:

Prof. Dr. Matthias Renz

Christian Beth, M.Sc.

Temporal HIN example from PANGAEA-dataset.

An example excerpt of the PANGAEA-dataset, modelled as a temporal HIN.

Abstract

Many correlations and real systems can be modeled as heterogeneous information networks (HIN). Other than homogeneous information networks a HIN is a directed graph containing more than one type of nodes or more than one type of edges. To measure the relevance of two of these nodes, we use Struct Count and Structure Constrained Subgraph Expansion (SCSE) for meta structures. These measurement methods differently indicate how much two nodes are related to a given meta structure.
Therefore we search for instances in the given graph topologically along with the layer of a meta structure. Meta structures describe the relationship of one node to another by indicating types of edges. As opposed to meta paths they are more expressive. Meta paths can be considered as special meta structures that have no branches.
Current publications do not consider temporal aspects measuring relevance with meta structures in HINs. For that reason, different concepts are presented in this thesis. Furthermore, we implement an HIN in Python with the help of the NetworkX package, we add Struct Count and SCSE to it and evaluate the new approaches.