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Temporal Evolution of Entity Relatedness using Wikipedia and DBpedia

Entity relatedness is a task that is required in many applications such as entity disambiguation and clustering. Although there are many works on entity relatedness, most of them do not consider temporal aspects and thus, it is unclear how entity relatedness changes over time. This paper attempts to address this gap by showing how entity relatedness develops over time with graph-based approaches using Wikipedia and DBpedia as well as how transient links and stable links, by which is meant links that do not persist over different times and links that persist over time respectively, affect the relatedness of the entities. We show that different versions of the knowledge base at different times give different accuracy on the KORE dataset, and show how using multiple versions of the knowledge base through time can increase the accuracy of entity relatedness over a version of the knowledge graph from a single time point.