@inproceedings{kauppinen-et-al-learning-eswc-2009,
  author = {Tomi Kauppinen and Kimmo Puputti and Panu Paakkarinen and Heini Kuittinen and Jari Väätäinen and Eero Hyvönen},
  title = {Learning and Visualizing Cultural Heritage Connections between Places on the Semantic Web},
  booktitle = {Proceedings of the Workshop on Inductive Reasoning and Machine Learning on the Semantic Web (IRMLeS2009), The 6th Annual European Semantic Web Conference (ESWC2009)},
  year = {2009},
  month = 	 {May 31 - June 4},
  OPTpages = {},
  OPTnote = {http://irmles2009.di.uniba.it/},
  OPTannote =    {semantic web,data mining,tag,collective intelligence},
  OPTproject =   {http://www.seco.hut.fi/projects/finnonto,http://www.seco.hut.fi/projects/smartmuseum,http://www.seco.hut.fi/projects/sw20,http://www.seco.tkk.fi/applications/kulttuurisampo/},
  abstract = {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 interestingness 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.}
}