| Abstract |
In recent years, there has been a growing interest from the Digital
Humanities in knowledge graphs as data modelling paradigm. Already, many
data sets have been published as such and are available in the Linked
Open Data cloud. With it, the nature of these data has shifted from
unstructured to structured. This presents new opportunities for data
mining. In this work, we investigate to what extend data mining can
contribute to the understanding of archaeological knowledge, expressed
as knowledge graph, and which form would best meet the communities'
needs. A case study was held which involved the user-driven mining of
generalized association rules. Experiments have shown that the approach
yielded mostly plausible patterns, some of which were seen as highly
relevant by domain experts. |