Learning and Visualizing Cultural Heritage Connections between Places on the Semantic Web
Tomi Kauppinen, Kimmo Puputti, Panu Paakkarinen, Heini Kuittinen, Jari Väätäinen, Eero Hyvönen · 2009
Semantic web techniques can be used to relate two things together. However, usually this relation is not accompanied with a measure that would tell how interesting the relation is. Data mining tradition provides interestingness measures; it is natural to try and fit semantic web and data mining traditions together. In this paper we use support and confidence values provided by association rule mining as interest measures for relations. The presented method is tailored to location ontologies in order to find out what interesting mutual relations two places have based on annotations in the cultural heritage domain. The method also uses ontology-based reasoning to group places together. We present tests of running the method against a set of over 60,000 annotations in order to find out cultural heritage connections between places.