@inproceedings{schmitz2006mining,
  address = {Berlin/Heidelberg},
  author = {Schmitz, Christoph and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd},
  booktitle = {Data Science and Classification (Proc. IFCS 2006 Conference)},
  doi = {10.1007/3-540-34416-0_28},
  editor = {Batagelj, V. and Bock, H.-H. and Ferligoj, A. and Žiberna, A.},
  interhash = {20650d852ca3b82523fcd8b63e7c12d7},
  intrahash = {c8dbb6371be8d67e3aa1928bd3dd0fed},
  isbn = {978-3-540-34415-5},
  month = {July},
  note = {Ljubljana},
  pages = {261-270},
  publisher = {Springer},
  series = {Studies in Classification, Data Analysis, and Knowledge Organization},
  title = {Mining Association Rules in Folksonomies},
  url = {http://www.kde.cs.uni-kassel.de/hotho/pub/2006/schmitz2006asso_ifcs.pdf},
  vgwort = {18},
  year = 2006
}

@incollection{bloehdorn2006learning,
  abstract = {Recent work has shown improvements in text clustering and classification tasks by integrating conceptual features extracted from ontologies. In this paper we present text mining experiments in the medical domain in which the ontological structures used are acquired automatically in an unsupervised learning process from the text corpus in question. We compare results obtained using the automatically learned ontologies with those obtained using manually engineered ones. Our results show that both types of ontologies improve results on text clustering and classification tasks, whereby the automatically acquired ontologies yield a improvement competitive with the manually engineered ones.
ER  -},
  author = {Bloehdorn, Stephan and Cimiano, Philipp and Hotho, Andreas},
  booktitle = {From Data and Information Analysis to Knowledge Engineering},
  doi = {http://dx.doi.org/10.1007/3-540-31314-1_40},
  interhash = {cf1af505b638677f00b3d3d7a5903199},
  intrahash = {bc1d40cf4fd64780ecf712b1e40f31de},
  isbn = {978-3-540-31313-7},
  pages = {334--341},
  publisher = {Springer Berlin Heidelberg},
  title = {Learning Ontologies to Improve Text Clustering and Classification},
  url = {http://www.kde.cs.uni-kassel.de/hotho/pub/2006/2006-03-gfkl05-bloehdorn-etal-learning-ontologies.pdf},
  year = 2006
}

@inproceedings{schmitz2006content,
  address = {Budva, Montenegro},
  author = {Schmitz, Christoph and Hotho, Andreas and J\"aschke, Robert and Stumme, Gerd},
  booktitle = {Proceedings of the 3rd European Semantic Web Conference},
  interhash = {940fa3c671c771cc9a644b3ecfef43cd},
  intrahash = {9a06428ec3bd72e3ea6c7a8f08e2bb85},
  isbn = {3-540-34544-2},
  month = {June},
  pages = {530-544},
  publisher = {Springer},
  series = {LNCS},
  title = {Content Aggregation on Knowledge Bases using Graph Clustering},
  url = {http://www.kde.cs.uni-kassel.de/hotho/pub/2006/schmitz2006sumarize_eswc.pdf},
  vgwort = {27},
  volume = 4011,
  year = 2006
}

@inproceedings{hotho2006information,
  address = {Budva, Montenegro},
  author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd},
  booktitle = {Proceedings of the 3rd European Semantic Web Conference },
  interhash = {10ec64d80b0ac085328a953bb494fb89},
  intrahash = {7da1127fc4836e2cf58e3073f1b888b2},
  isbn = {3-540-34544-2},
  month = {June},
  pages = {411-426},
  publisher = {Springer},
  series = {LNCS},
  title = {Information Retrieval in Folksonomies: Search and Ranking},
  url = {http://www.kde.cs.uni-kassel.de/hotho/pub/2006/seach2006hotho_eswc.pdf},
  vgwort = {29},
  volume = 4011,
  year = 2006
}

@inproceedings{hoser2006semantic,
  address = {Budva, Montenegro},
  author = {Hoser, Bettina and Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd},
  booktitle = {Proceedings of the 3rd European Semantic Web Conference},
  interhash = {344ec3b4ee8af1a2c6b86efc14917fa9},
  intrahash = {85f032bf2ffe9b1b55f8656c8a0d6d70},
  isbn = {3-540-34544-2},
  month = {June},
  pages = {514-529},
  publisher = {Springer},
  series = {LNCS},
  title = {Semantic Network Analysis of Ontologies},
  url = {http://www.kde.cs.uni-kassel.de/hotho/pub/2006/hoser_sna_eswc2005.pdf},
  vgwort = {29},
  volume = 4011,
  year = 2006
}