Unsupervised generation of data mining features from linked open data

@inproceedings{Paulheim2012UnsupervisedGO,
  title={Unsupervised generation of data mining features from linked open data},
  author={Heiko Paulheim and Johannes F{\"u}rnkranz},
  booktitle={WIMS},
  year={2012}
}
The quality of the results of a data mining process strongly depends on the quality of the data it processes. A good result is more likely to obtain the more useful background knowledge there is in a dataset. In this paper, we present a fully automatic approach for enriching data with features that are derived from Linked Open Data, a very large, openly available data collection. We identify six different types of feature generators, which are implemented in our open-source tool FeGeLOD. In… CONTINUE READING
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