@techreport{stumme99conceptualknowledge,
  author = {Stumme, G.},
  comment = {alpha},
  institution = {TU Darmstadt},
  interhash = {c33970150f97bad7972281e38b42738f},
  intrahash = {6d562dc043ba698acee8a83ce35bde6e},
  title = {Conceptual Knowledge Discovery with Frequent Concept Lattices},
  type = {{FB}4-{P}reprint 2043},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/1999/P2043.pdf},
  year = 1999
}

@inproceedings{bastide00levelwise,
  address = {France},
  author = {Bastide, Y. and Taouil, R. and Pasquier, N. and Stumme, G. and Lakhal, L.},
  booktitle = {Actes des 16ièmes Journées Bases de Données Avancées},
  comment = {alpha},
  interhash = {a3181cc73b190099592107cf465c4e43},
  intrahash = {a11de6a74851c7076452159d1b12489b},
  month = {Oct 24-27},
  pages = {307-322},
  publisher = {Blois},
  title = {Levelwise Search of Frequent Patterns},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2000/BDA00.pdf},
  year = 2000
}

@inproceedings{bastide00miningminimal,
  address = {Heidelberg},
  author = {Bastide, Y. and Pasquier, N. and Taouil, R. and Stumme, G. and Lakhal, L.},
  booktitle = {Computational Logic --- CL 2000 Proc. CL'00},
  editor = {Lloyd, J. and Dahl, V. and Furbach, U. and Kerber, M. and Laus, K.-K. and Palamidessi, C. and Pereira, L.M. and Sagiv, Y. and Stuckey, P.J.},
  interhash = {dc10d0ad3c40463f049ac775cb250f3d},
  intrahash = {25fa3431e7bdd7057f9b80a7385cd718},
  page = {972-986},
  publisher = {Springer},
  series = {LNAI},
  title = {Mining Minimal Non-Redundant Association Rules Using Frequent Closed Itemsets},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2000/DOOD00.pdf},
  volume = 1861,
  year = 2000
}

@article{bastide00miningfrequent,
  author = {Bastide, Y. and Taouil, R. and Pasquier, N. and Stumme, G. and Lakhal, L.},
  interhash = {86c9586115ef1c7ec8539257849d9842},
  intrahash = {1e79f8ba76044d2c78cea441eeba84aa},
  journal = {SIGKDD Explorations, Special Issue on Scalable Algorithms},
  number = 2,
  pages = {71-80},
  title = {Mining Frequent Patterns with Counting Inference.},
  volume = 2,
  year = 2000
}