@inproceedings{stumme02efficient,
  address = {Heidelberg},
  author = {Stumme, G.},
  booktitle = {Database and Expert Systems Applications. Proc. DEXA 2002},
  editor = {Hameurlain, A. and Cicchetti, R. and Traunmüller, R.},
  interhash = {56611a15d60e2711a0aafc257715c03d},
  intrahash = {0adce6a0db24566bb55d6e2d6667c8e7},
  pages = {534-546},
  publisher = {Springer},
  series = {LNCS},
  title = {Efficient Data Mining Based on Formal Concept Analysis},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2002/DEXA02.pdf},
  volume = 2453,
  year = 2002
}

@proceedings{stumme01semantic,
  address = {Freiburg},
  editor = {Stumme, G. and Hotho, A. and Berendt, B.},
  interhash = {8e0ea487e66cca158e69263d18d856f8},
  intrahash = {ee4f8a6316e6454df268067b4e47f818},
  month = {September 3rd,},
  title = {Semantic Web Mining. Workshop Proceedings.},
  url = {http://semwebmine2001.aifb.uni-karlsruhe.de/online.html},
  year = 2001
}

@inproceedings{stumme01conceptualclustering,
  address = {Universität Dortmund 763},
  author = {Stumme, G. and Taouil, R. and Bastide, Y. and Lakhal, L.},
  booktitle = {Proc. GI-Fachgruppentreffen Maschinelles Lernen (FGML'01)},
  editor = {Klinkenberg, R. and Rüping, S. and Fick, A. and Henze, N. and Herzog, C. and Molitor, R. and Schröder, O.},
  interhash = {c99f2ae002435208c58f9244d298a10b},
  intrahash = {f4ec21d5f63dbc213a3a6eae076c4b62},
  month = {October},
  title = {Conceptual  Clustering  with  Iceberg  Concept Lattices},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2001/FGML01.pdf},
  year = 2001
}

@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
}

@inproceedings{hereth2000conceptual,
  address = {Heidelberg},
  author = {Hereth, J. and Stumme, G. and Wille, R. and Wille, U.},
  booktitle = {Conceptual Structures: Logical, Linguistic, and Computational  Issues. Proc. ICCS '00},
  editor = {Ganter, B. and Mineau, G. W.},
  interhash = {8a4c0c21d83c25bb78f80e89dd36a89a},
  intrahash = {577e0f2074bbece17498848014d14705},
  page = {{P}art of \cite{hereth03conceptual}},
  pages = {421-437},
  publisher = {Springer},
  series = {LNAI},
  title = {Conceptual Knowledge Discovery and Data Analysis},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2000/P2092_ICCS00_kdd.pdf},
  volume = 1867,
  year = 2000
}

@inproceedings{stumme01intelligent,
  address = {Heidelberg},
  author = {Stumme, G. and Taouil, R. and Bastide, Y. and Pasquier, N. and Lakhal, L.},
  booktitle = {KI 2001: Advances in Artificial Intelligence. KI 2001},
  editor = {Baader, F. and Brewker, G. and Eiter, T.},
  interhash = {15d7d015c8820a41323ab4e7639ff151},
  intrahash = {d93292a7637bd2061b67f4934e7dde46},
  pages = {335-350},
  publisher = {Springer},
  series = {LNAI},
  title = {Intelligent Structuring and Reducing of Association Rules and with Formal Concept Analysis},
  url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2001/KI01.pdf},
  volume = 2174,
  year = 2001
}

@article{AnkEtAl99,
  abstract = {Cluster analysis is a primary method for database mining. It is either used as a stand-alone tool to get insight into the distribution of a data set, e.g. to focus further analysis and data processing, or as a preprocessing step for other algorithms operating on the detected clusters. Almost all of the well-known clustering algorithms require input parameters which are hard to determine but have a significant influence on the clustering result. Furthermore, for many real-data sets there does not even exist a global parameter setting for which the result of the clustering algorithm describes the intrinsic clustering structure accurately. We introduce a new algorithm for the purpose of cluster analysis which does not produce a clustering of a data set explicitly; but instead creates an augmented ordering of the database representing its density-based clustering structure. This cluster-ordering contains information which is equivalent to the density-based clusterings corresponding to a broad range of parameter settings. It is a versatile basis for both automatic and interactive cluster analysis. We show how to automatically and efficiently extract not only 'traditional' clustering information (e.g. representative points, arbitrary shaped clusters), but also the intrinsic clustering structure. For medium sized data sets, the cluster-ordering can be represented graphically and for very large data sets, we introduce an appropriate visualization technique. Both are suitable for interactive exploration of the intrinsic clustering structure offering additional insights into the distribution and correlation of the data.},
  address = {New York, NY, USA},
  author = {Ankerst, Mihael and Breunig, Markus M. and Kriegel, Hans-Peter and Sander, J?rg},
  doi = {http://doi.acm.org/10.1145/304181.304187},
  interhash = {7417e17c0e8eec9f1a9f2bc57a476b15},
  intrahash = {86b1a51b501c882f9a4f1cdacca3f7ed},
  issn = {0163-5808},
  journal = {ACM SIGMOD Record},
  number = 2,
  pages = {49--60},
  publisher = {ACM},
  title = {OPTICS: Ordering Points to Identify the Clustering Structure},
  url = {http://portal.acm.org/citation.cfm?id=304187},
  volume = 28,
  year = 1999
}

@incollection{fayyad1996data,
  abstract = {Data mining and knowledge discovery in
databases have been attracting a significant amount of research, industry, and media attention of late. What is all the excitement about? This article provides an overview of this emerging
field, clarifying how data mining and knowledge discovery in databases are related both to each other and to related fields, such as machine learning, statistics, and databases. The article
mentions particular real-world applications, specific data-mining techniques, challenges involved in real-world applications of knowledge
discovery, and current and future research directions in the field.},
  address = {Menlo Park, CA, USA},
  author = {Fayyad, Usama M. and Piatetsky-Shapiro, Gregory and Smyth, Padhraic},
  booktitle = {Advances in knowledge discovery and data mining},
  editor = {Fayyad, Usama M. and Piatetsky-Shapiro, Gregory and Smyth, Padhraic and Uthurusamy, Ramasamy},
  interhash = {79663e4b1f464b82ce1ae45345dc424f},
  intrahash = {3f5a400d01a974f993cee1ac5f79cfc8},
  isbn = {0-262-56097-6},
  pages = {1--34},
  publisher = {American Association for Artificial Intelligence},
  title = {From data mining to knowledge discovery: an overview},
  url = {http://portal.acm.org/citation.cfm?id=257942},
  year = 1996
}

@incollection{books/mit/fayyadPSU96/FayyadPS96,
  author = {Fayyad, Usama M. and Piatetsky-Shapiro, Gregory and Smyth, Padhraic},
  booktitle = {Advances in Knowledge Discovery and Data Mining},
  date = {2002-01-03},
  interhash = {79663e4b1f464b82ce1ae45345dc424f},
  intrahash = {e59886c68d1fc9bb4d1a8d6a1a644a60},
  pages = {1-34},
  title = {From Data Mining to Knowledge Discovery: An Overview.},
  url = {http://dblp.uni-trier.de/db/books/collections/fayyad96.html#FayyadPS96},
  year = 1996
}

@incollection{1420085867,
  asin = {1420085867},
  author = {May, Michael and Berendt, Bettina and Cornuéjols, Antoine and Gama, Jõao and Giannotti, Fosca and Hotho, Andreas and Malerba, Donato and Menesalvas, Ernestina and Morik, Katharina and Pedersen, Rasmus and Saitta, Lorenza and Saygin, Yücel and Schuster, Assaf and Vanhoof, Koen},
  booktitle = {Next Generation of Data Mining (Chapman & Hall/Crc Data Mining and Knowledge Discovery Series)},
  dewey = {005.74},
  ean = {9781420085860},
  edition = 1,
  interhash = {7aeb3b998b5918d86093e05601e81b4d},
  intrahash = {be3c753af98ab591b4f31d349513b461},
  isbn = {1420085867},
  isbn13 = {9781420085860},
  publisher = {Chapman & Hall/CRC},
  title = {Research Challenges in Ubiquitous Knowledge Discovery},
  url = {http://208.254.79.11/shopping_cart/products/product_contents.asp?id=&parent_id=497&sku=C5867&isbn=9781420085860&pc=},
  year = 2008
}

@inbook{Mladenic2008KD,
  author = {Mladenic, D. and Grobelnik, M. and Fortuna, B. and Grcar, M.},
  booktitle = {Semantic Knowledge Management: Integrating Ontology Management, Knowledge Discovery, and Human Language Technologies },
  date = {(2008)Springer 2008},
  editor = {Davies, John and Grobelnik, Marko and Mladenic, Dunja},
  interhash = {b51ab03fe53193ea93c9965038d8215e},
  intrahash = {c65415ccb54615b32ee167ea639c8177},
  location = {Grobelnik, Mladenic(eds. )},
  title = {Knowledge Discovery for Semantic Web},
  year = 2008
}

@article{wille02why,
  author = {Wille, Rudolf},
  date = {2004-02-13},
  ee = {http://taylorandfrancis.metapress.com/openurl.asp?genre=article&issn=0952-813x&volume=14&issue=2&spage=81},
  interhash = {c214a68383b61756ff05b64d8098afea},
  intrahash = {dd266b193c76d6cb46be6afa3e9396bb},
  journal = {J. Exp. Theor. Artif. Intell.},
  number = {2-3},
  pages = {81-92},
  title = {Why can concept lattices support knowledge discovery in databases?},
  url = {http://dblp.uni-trier.de/db/journals/jetai/jetai14.html#Wille02},
  volume = 14,
  year = 2002
}

@inproceedings{boulicaut00approximation,
  author = {Boulicaut, Jean-Francois and Bykowski, Artur and Rigotti, Christophe},
  booktitle = {Principles of Data Mining and Knowledge Discovery},
  interhash = {bcaa8a570d6b987b6171c4b7aff7cacd},
  intrahash = {7e53b931a9ba3d36c7536f31901376bf},
  pages = {75-85},
  title = {Approximation of Frequency Queris by Means of Free-Sets},
  url = {citeseer.ist.psu.edu/boulicaut00approximation.html},
  year = 2000
}

@inbook{baldi03modelling,
  abstract = {Modeling the Internet and the Web covers the most important aspects of modeling the Web using a modern mathematical and probabilistic treatment. It focuses on the information and application layers, as well as some of the emerging properties of the Internet.  Provides a comprehensive introduction to the modeling of the Internet and the Web at the information level.  Takes a modern approach based on mathematical, probabilistic, and graphical modeling.  Provides an integrated presentation of theory, examples, exercises and applications.  Covers key topics such as text analysis, link analysis, crawling techniques, human behaviour, and commerce on the Web. Interdisciplinary in nature, Modeling the Internet and the Web will be of interest to students and researchers from a variety of disciplines including computer science, machine learning, engineering, statistics, economics, business, and the social sciences.},
  author = {Baldi, Pierre and Frasconi, Paolo and Smyth, Padhraic},
  booktitle = {Modeling the Internet and the Web: Probabilistic Methods and Algorithms},
  citeulike-article-id = {822915},
  interhash = {416f2405193ae7d30cffe673dee89df2},
  intrahash = {3e4e2899e7d6988218d02a264bcfe24a},
  month = {April},
  priority = {2},
  publisher = {Wiley},
  title = {Modeling the Internet and the Web: Probabilistic Methods and Algorithms},
  url = {http://eu.wiley.com/WileyCDA/WileyTitle/productCd-0470849061.html},
  year = 2003
}

@proceedings{DBLP:conf/kdd/1999web,
  bibsource = {DBLP, http://dblp.uni-trier.de},
  booktitle = {WEBKDD},
  editor = {Masand, Brij M. and Spiliopoulou, Myra},
  interhash = {29a69416c66bd604c4599009915dc0b0},
  intrahash = {18a9697e8ca04f637487e79b6be9cc83},
  isbn = {3-540-67818-2},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  title = {Web Usage Analysis and User Profiling, International WEBKDD'99
               Workshop, San Diego, California, USA, August 15, 1999, Revised
               Papers},
  volume = 1836,
  year = 2000
}

@book{books/mk/Pyle99,
  author = {Pyle, Dorian},
  date = {2002-01-28},
  interhash = {3edec307e8a02fa778ee847eccfb4215},
  intrahash = {29f6bc4833269393dabf92bae3afa905},
  isbn = {1-55860-529-0},
  publisher = {Morgan Kaufmann},
  title = {Data Preparation for Data Mining},
  year = 1999
}

@inproceedings{conf/sigmod/NgLHP98,
  author = {Ng, Raymond T. and Lakshmanan, Laks V. S. and Han, Jiawei and Pang, Alex},
  booktitle = {SIGMOD Conference},
  cdrom = {SIGMOD98/P013.PDF},
  cite = {conf/sigmod/AgrawalIS93},
  ee = {db/conf/sigmod/NgLHP98.html},
  interhash = {c4e73bae8e22a39d15d022631c69ddbf},
  intrahash = {72825e6a12b3285349fb64c1020383c0},
  pages = {13-24},
  title = {Exploratory Mining and Pruning Optimizations of Constrained Association Rules.},
  url = {http://dblp.uni-trier.de/db/conf/sigmod/sigmod98.html#NgLHP98},
  year = 1998
}

@inproceedings{672836,
  address = {San Francisco, CA, USA},
  author = {Agrawal, Rakesh and Srikant, Ramakrishnan},
  booktitle = {VLDB '94: Proceedings of the 20th International Conference on Very Large Data Bases},
  interhash = {960c924ccbe1ff429a30f7433ec53122},
  intrahash = {cce11d670329a38a90f625b8005dfb8d},
  isbn = {1-55860-153-8},
  pages = {487--499},
  publisher = {Morgan Kaufmann Publishers Inc.},
  title = {Fast Algorithms for Mining Association Rules in Large Databases},
  year = 1994
}

@article{park1995ehb,
  author = {Park, J.S. and Chen, M.S. and Yu, P.S.},
  interhash = {e7a28762e92ab579ed3f99c565848f9a},
  intrahash = {094af08c931c876e20fd0e1e5086583b},
  journal = {Proceedings of the 1995 ACM SIGMOD international conference on Management of data},
  pages = {175-186},
  publisher = {ACM Press New York, NY, USA},
  title = {{An effective hash-based algorithm for mining association rules}},
  year = 1995
}