@article{Keim96, author = {Keim, D. and Kriegel, H.}, title = {Visualization techniques for mining large databases : A comparison}, journal = {IEEE Transactions on Knowledge and Data Engineering}, publisher = {IEEE Computer Society Press}, year = {1996}, volume = {8}, number = {6}, pages = {923--938}, keywords = {FCA, OntologyHandbook} }

%0 = article %A = Keim, D. and Kriegel, H. %D = 1996 %I = IEEE Computer Society Press %T = Visualization techniques for mining large databases : A comparison

@incollection{stumme02using, author = {Stumme, G.}, title = {Using Ontologies and Formal Concept Analysis for Organizing Business Knowledge}, editor = {Becker, J. and Knackstedt, R.}, booktitle = {Wissensmanagement mit Referenzmodellen -- Konzepte für die Anwendungssystem- und Organisationsgestaltung}, publisher = {Physica}, address = {Heidelberg}, year = {2002}, pages = {163-174}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2001/REFMOD01.ps}, keywords = {2002, analysis, business, concept, fca, formal, knowledge, management, myown, ontologies, semantic, web, wissensmanagement} }

%0 = incollection %A = Stumme, G. %B = Wissensmanagement mit Referenzmodellen -- Konzepte für die Anwendungssystem- und Organisationsgestaltung %C = Heidelberg %D = 2002 %I = Physica %T = Using Ontologies and Formal Concept Analysis for Organizing Business Knowledge %U = http://www.kde.cs.uni-kassel.de/stumme/papers/2001/REFMOD01.ps

@book{habermas81theorie, author = {Habermas, J�rgen}, title = {Theorie des kommunikativen Handelns}, publisher = {Suhrkamp}, address = {Frankfurt}, year = {1981}, keywords = {FCA, OntologyHandbook, fca, habermas, handeln, handelns, kommunikativen, kommunikatives, theorie} }

%0 = book %A = Habermas, J�rgen %C = Frankfurt %D = 1981 %I = Suhrkamp %T = Theorie des kommunikativen Handelns

@techreport{GH05structure, author = {Golder, Scott and Huberman, Bernardo A.}, title = {The Structure of Collaborative Tagging Systems}, year = {2005}, url = {http://arxiv.org/abs/cs.DL/0508082}, keywords = {FCA, OntologyHandbook, folksonomy, structure, tagging} }

%0 = techreport %A = Golder, Scott and Huberman, Bernardo A. %B = } %C = %D = 2005 %I = %T = The Structure of Collaborative Tagging Systems} %U = http://arxiv.org/abs/cs.DL/0508082

Topics in education are changing with an ever faster pace. E-Learning
sources tend to be more and more decentralised. Users need increasingly to be able to
e the resources of the web. For this, they should have tools for finding and organizing
formation in a decentral way. In this, paper, we show how an ontology-based tool
ite allows to make the most of the resources available on the web.

@inproceedings{tane03courseware, author = {Tane, Julien and Schmitz, Christoph and Stumme, Gerd and Staab, Steffen and Studer, R.}, title = {The Courseware Watchdog: an Ontology-based tool for finding and organizing
learning material}, editor = {David, Klaus and Wegner, Lutz}, booktitle = {Mobiles Lernen und Forschen - Beiträge der Fachtagung an der Universität}, publisher = {Kassel University Press}, year = {2003}, pages = {93-104}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2003/tane2003courseware.pdf}, keywords = {2003, analysis, concept, courseware, crawling, e-learning, eLearning, edutella, fca, formal, myown, ontologies, ontology, p2p, padlr, watchdog}, abstract = {Topics in education are changing with an ever faster pace. E-Learning
sources tend to be more and more decentralised. Users need increasingly to be able to
e the resources of the web. For this, they should have tools for finding and organizing
formation in a decentral way. In this, paper, we show how an ontology-based tool
ite allows to make the most of the resources available on the web.} }

%0 = inproceedings %A = Tane, Julien and Schmitz, Christoph and Stumme, Gerd and Staab, Steffen and Studer, R. %B = Mobiles Lernen und Forschen - Beiträge der Fachtagung an der Universität %D = 2003 %I = Kassel University Press %T = The Courseware Watchdog: an Ontology-based tool for finding and organizing
learning material %U = http://www.kde.cs.uni-kassel.de/stumme/papers/2003/tane2003courseware.pdf

Formal Concept Analysis (FCA) is an unsupervised clustering technique and many scientific papers are devoted to applying FCA in Information Retrieval (IR) research. We collected 103 papers published between 2003-2009 which mention FCA and information retrieval in the abstract, title or keywords. Using a prototype of our FCA-based toolset CORDIET, we converted the pdf-files containing the papers to plain text, indexed them with Lucene using a thesaurus containing terms related to FCA research and then created the concept lattice shown in this paper. We visualized, analyzed and explored the literature with concept lattices and discovered multiple interesting research streams in IR of which we give an extensive overview. The core contributions of this paper are the innovative application of FCA to the text mining of scientific papers and the survey of the FCA-based IR research.

@incollection{noKey, author = {Poelmans, Jonas and Ignatov, DmitryI. and Viaene, Stijn and Dedene, Guido and Kuznetsov, SergeiO.}, title = {Text Mining Scientific Papers: A Survey on FCA-Based Information Retrieval Research}, editor = {Perner, Petra}, booktitle = {Advances in Data Mining. Applications and Theoretical Aspects}, series = {Lecture Notes in Computer Science}, publisher = {Springer Berlin Heidelberg}, year = {2012}, volume = {7377}, pages = {273-287}, url = {http://dx.doi.org/10.1007/978-3-642-31488-9_22}, doi = {10.1007/978-3-642-31488-9_22}, isbn = {978-3-642-31487-2}, keywords = {FCA, IR, Mining, SOTA, Text}, abstract = {Formal Concept Analysis (FCA) is an unsupervised clustering technique and many scientific papers are devoted to applying FCA in Information Retrieval (IR) research. We collected 103 papers published between 2003-2009 which mention FCA and information retrieval in the abstract, title or keywords. Using a prototype of our FCA-based toolset CORDIET, we converted the pdf-files containing the papers to plain text, indexed them with Lucene using a thesaurus containing terms related to FCA research and then created the concept lattice shown in this paper. We visualized, analyzed and explored the literature with concept lattices and discovered multiple interesting research streams in IR of which we give an extensive overview. The core contributions of this paper are the innovative application of FCA to the text mining of scientific papers and the survey of the FCA-based IR research.} }

%0 = incollection %A = Poelmans, Jonas and Ignatov, DmitryI. and Viaene, Stijn and Dedene, Guido and Kuznetsov, SergeiO. %B = Advances in Data Mining. Applications and Theoretical Aspects %D = 2012 %I = Springer Berlin Heidelberg %T = Text Mining Scientific Papers: A Survey on FCA-Based Information Retrieval Research %U = http://dx.doi.org/10.1007/978-3-642-31488-9_22

Text document clustering plays an important role in providing intuitive
vigation and browsing mechanisms by organizing large amounts of information
to a small number of meaningful clusters. Standard partitional or agglomerative
ustering methods efficiently compute results to this end.
wever, the bag of words representation used for these clustering methods is often
satisfactory as it ignores relationships between important terms that do not
-occur literally. Also, it is mostly left to the user to find out why a particular partitioning
s been achieved, because it is only specified extensionally. In order to
al with the two problems, we integrate background knowledge into the process of
ustering text documents.
rst, we preprocess the texts, enriching their representations by background knowledge
ovided in a core ontology — in our application Wordnet. Then, we cluster
e documents by a partitional algorithm. Our experimental evaluation on Reuters
wsfeeds compares clustering results with pre-categorizations of news. In the experiments,
provements of results by background knowledge compared to the baseline
n be shown for many interesting tasks.
cond, the clustering partitions the large number of documents to a relatively small
mber of clusters, which may then be analyzed by conceptual clustering. In our approach,
applied Formal Concept Analysis. Conceptual clustering techniques are
own to be too slow for directly clustering several hundreds of documents, but they
ve an intensional account of cluster results. They allow for a concise description
commonalities and distinctions of different clusters. With background knowledge
ey even find abstractions like “food” (vs. specializations like “beef” or “corn”).
us, in our approach, partitional clustering reduces first the size of the problem
ch that it becomes tractable for conceptual clustering, which then facilitates the
derstanding of the results.

@techreport{hotho03textclustering, author = {Hotho, Andreas and Staab, Steffen and Stumme, Gerd}, title = {Text Clustering Based on Background Knowledge}, type = {Technical Report }, year = {2003}, volume = {425}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2003/hotho2003text.pdf}, keywords = {2003, analysis, background, clustering, concept, fca, formal, knowledge, myown, ontologies, semantic, text, web}, abstract = {Text document clustering plays an important role in providing intuitive navigation and browsing mechanisms by organizing large amounts of information into a small number of meaningful clusters. Standard partitional or agglomerative clustering methods efficiently compute results to this end. However, the bag of words representation used for these clustering methods is often unsatisfactory as it ignores relationships between important terms that do not co-occur literally. Also, it is mostly left to the user to find out why a particular partitioning has been achieved, because it is only specified extensionally. In order to deal with the two problems, we integrate background knowledge into the process of clustering text documents. First, we preprocess the texts, enriching their representations by background knowledge provided in a core ontology — in our application Wordnet. Then, we cluster the documents by a partitional algorithm. Our experimental evaluation on Reuters newsfeeds compares clustering results with pre-categorizations of news. In the experiments, improvements of results by background knowledge compared to the baseline can be shown for many interesting tasks. Second, the clustering partitions the large number of documents to a relatively small number of clusters, which may then be analyzed by conceptual clustering. In our approach, we applied Formal Concept Analysis. Conceptual clustering techniques are known to be too slow for directly clustering several hundreds of documents, but they give an intensional account of cluster results. They allow for a concise description of commonalities and distinctions of different clusters. With background knowledge they even find abstractions like “food” (vs. specializations like “beef” or “corn”). Thus, in our approach, partitional clustering reduces first the size of the problem such that it becomes tractable for conceptual clustering, which then facilitates the understanding of the results.} }

%0 = techreport %A = Hotho, Andreas and Staab, Steffen and Stumme, Gerd %B = } %C = %D = 2003 %I = %T = Text Clustering Based on Background Knowledge} %U = http://www.kde.cs.uni-kassel.de/stumme/papers/2003/hotho2003text.pdf

@inproceedings{Houtsma95, author = {Houtsma, M. and Swami, A.}, title = {Set-oriented mining for association rules in relational databases}, booktitle = {Proceedings of the 11th International Conference on Data Engineering
(ICDE'95)}, publisher = {IEEE Computer Society Press}, year = {1995}, pages = {25--33}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Houtsma, M. and Swami, A. %B = Proceedings of the 11th International Conference on Data Engineering
(ICDE'95) %D = 1995 %I = IEEE Computer Society Press %T = Set-oriented mining for association rules in relational databases

@inproceedings{tane04semantic, author = {Tane, Julien and Schmitz, Christoph and Stumme, Gerd}, title = {Semantic resource management for the web: an e-learning application}, booktitle = {Proc. 13th International World Wide Web Conference (WWW 2004)}, year = {2004}, pages = {1-10}, url = {http://www.www2004.org/proceedings/docs/2p1.pdf}, keywords = {2004, application, courseware, crawler, e-learning, eLearning, edutella, fca, itegpub, l3s, learning, myown, p2p, semantic, watchdog, web} }

%0 = inproceedings %A = Tane, Julien and Schmitz, Christoph and Stumme, Gerd %B = Proc. 13th International World Wide Web Conference (WWW 2004) %D = 2004 %T = Semantic resource management for the web: an e-learning application %U = http://www.www2004.org/proceedings/docs/2p1.pdf

@inproceedings{hereth01reverse, author = {Hereth, J. and Stumme, G.}, title = {Reverse Pivoting in Conceptual Information Systems.}, editor = {Delugach, H. and Stumme, G.}, booktitle = {Conceptual Structures: Broadening the Base. }, series = {LNAI}, publisher = {Springer}, address = {Heidelberg}, year = {2001}, volume = {2120}, pages = {202-215}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2001/ICCS01.pdf}, keywords = {2001, analysis, concept, conceptual, fca, formal, information, myown, pivoting, reverse, systems, toscana} }

%0 = inproceedings %A = Hereth, J. and Stumme, G. %B = Conceptual Structures: Broadening the Base. %C = Heidelberg %D = 2001 %I = Springer %T = Reverse Pivoting in Conceptual Information Systems. %U = http://www.kde.cs.uni-kassel.de/stumme/papers/2001/ICCS01.pdf

@inproceedings{HerethStumme01Reverse, author = {Hereth, J. and Stumme, G.}, title = {Reverse Pivoting in Conceptual Information Systems}, editor = {Delugach, H. S. and Stumme, G.}, booktitle = {Conceptual Structures: Broadening the Base}, series = {Lecture Notes in Computer Science}, publisher = {Springer}, year = {2001}, volume = {2120}, pages = {202-215}, isbn = {3-540-42344-3}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Hereth, J. and Stumme, G. %B = Conceptual Structures: Broadening the Base %D = 2001 %I = Springer %T = Reverse Pivoting in Conceptual Information Systems

@inproceedings{Hereth02Relational, author = {Hereth, J.}, title = {Relational Scaling and Databases}, editor = {Priss, U. and Corbett, D. and Angelova, G.}, booktitle = {Conceptual Structures: Integration and Interfaces, 10th International
Conference on Conceptual Structures, ICCS 2002, Borovets, Bulgaria,
July 15-19, 2002, Proceedings}, series = {Lecture Notes in Computer Science}, publisher = {Springer}, year = {2002}, volume = {2393}, pages = {62-76}, isbn = {3-540-43901-3}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Hereth, J. %B = Conceptual Structures: Integration and Interfaces, 10th International
Conference on Conceptual Structures, ICCS 2002, Borovets, Bulgaria,
July 15-19, 2002, Proceedings %D = 2002 %I = Springer %T = Relational Scaling and Databases

We present an analysis of the publication and citation networks of all previous editions of the three conferences most relevant to the FCA community: ICFCA, ICCS and CLA. Using data mining methods from FCA and graph analysis, we investigate patterns and communities among authors, we identify and visualize influential publications and authors, and we give a statistical summary of the conferences’ history.

@inproceedings{doerfel2012publication, author = {Doerfel, Stephan and Jäschke, Robert and Stumme, Gerd}, title = {Publication Analysis of the Formal Concept Analysis Community}, editor = {Domenach, F. and Ignatov, D.I. and Poelmans, J.}, booktitle = {ICFCA 2012}, series = {Lecture Notes in Artificial Intelligence}, publisher = {Springer}, address = {Berlin/Heidelberg}, year = {2012}, volume = {7278}, pages = {77--95}, url = {https://www.kde.cs.uni-kassel.de/pub/pdf/doerfel2012publication.pdf}, keywords = {2012, analysis, community, concept, fca, home, info20pub, itegpub, l3s, myown, scientometrics}, abstract = {We present an analysis of the publication and citation networks of all previous editions of the three conferences most relevant to the FCA community: ICFCA, ICCS and CLA. Using data mining methods from FCA and graph analysis, we investigate patterns and communities among authors, we identify and visualize influential publications and authors, and we give a statistical summary of the conferences’ history.
} }

%0 = inproceedings %A = Doerfel, Stephan and Jäschke, Robert and Stumme, Gerd %B = ICFCA 2012 %C = Berlin/Heidelberg %D = 2012 %I = Springer %T = Publication Analysis of the Formal Concept Analysis Community %U = https://www.kde.cs.uni-kassel.de/pub/pdf/doerfel2012publication.pdf

@inproceedings{wille94plaedoyer, author = {Wille, Rudolf}, title = {Plädoyer für eine philosophische Grundlegung der Begrifflichen Wissensverarbeitung}, editor = {Wille, R. and Zickwolff, M.}, booktitle = {Begriffliche Wissensverarbeitung -- Grundfragen und Aufgaben}, journal = {B. I. -Wissenschaftsverlag}, publisher = {B. I. -Wissenschaftsverlag}, address = {Mannheim}, year = {1994}, pages = {11-25}, keywords = {FCA, OntologyHandbook, analysis, begriffliche, concept, conceptual, fca, formal, knowledge, processing, wissensverarbeitung} }

%0 = inproceedings %A = Wille, Rudolf %B = Begriffliche Wissensverarbeitung -- Grundfragen und Aufgaben %C = Mannheim %D = 1994 %I = B. I. -Wissenschaftsverlag %T = Plädoyer für eine philosophische Grundlegung der Begrifflichen Wissensverarbeitung

@book{brugger76philosophisches, author = {Brugger, W.}, title = {Philosophisches W�rterbuch}, publisher = {Herder}, address = {Freiburg}, year = {1976}, keywords = {FCA, OntologyHandbook, Philosophie, philosophy} }

%0 = book %A = Brugger, W. %C = Freiburg %D = 1976 %I = Herder %T = Philosophisches W�rterbuch

@inproceedings{stumme98online, author = {Stumme, Gerd}, title = {On-Line Analytical Processing with Conceptual Information Systems}, editor = {Tanaka, K. and Ghandeharizadeh, S.}, booktitle = {Proc. 5th Intl. Conf. on Foundations of Data Organization (FODO'98)}, year = {1998}, pages = {117-126}, note = {Short version of testumme00conceptual}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/1998/FODO98.pdf}, keywords = {1998, OntologyHandbook, analysis, analytical, concept, conceptual, fca, formal, myown, olap, online, processing} }

%0 = inproceedings %A = Stumme, Gerd %B = Proc. 5th Intl. Conf. on Foundations of Data Organization (FODO'98) %D = 1998 %T = On-Line Analytical Processing with Conceptual Information Systems %U = http://www.kde.cs.uni-kassel.de/stumme/papers/1998/FODO98.pdf

@inproceedings{goethals05mining, author = {Goethals, Bart and Muhonen, Juhu and Toivonen, Hannu}, title = {Mining non-derivable association rules}, booktitle = {Proc. SIAM International Conference on Data Mining}, address = {Newport Beach, CA}, year = {2005}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Goethals, Bart and Muhonen, Juhu and Toivonen, Hannu %B = Proc. SIAM International Conference on Data Mining %C = Newport Beach, CA %D = 2005 %T = Mining non-derivable association rules

@unpublished{Koperski98, author = {Koperski, K. and Han, J. and Adhikary, J.}, title = {Mining knowledge in geographical data}, year = {1998}, note = {Technical Report. ftp://ftp.fas.sfu.ca/pub/cs/han/ kdd/geosurvey98.ps}, keywords = {FCA, OntologyHandbook} }

%0 = unpublished %A = Koperski, K. and Han, J. and Adhikary, J. %B = } %C = %D = 1998 %I = %T = Mining knowledge in geographical data} %U =

@inproceedings{Han00mining, author = {Han, J. and Pei, J. and Yin, Y.}, title = {Mining frequent patterns without candidate generation.}, booktitle = {Proc. ACM SIGMOD Int'l Conf. on Management of Data}, year = {2000}, pages = {1--12}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Han, J. and Pei, J. and Yin, Y. %B = Proc. ACM SIGMOD Int'l Conf. on Management of Data %D = 2000 %T = Mining frequent patterns without candidate generation.

Social bookmark tools are rapidly emerging on the Web. In such
stems users are setting up lightweight conceptual structures
lled folksonomies. These systems provide currently relatively few
ructure. We discuss in this paper, how association rule mining
n be adopted to analyze and structure folksonomies, and how the results can be used
r ontology learning and supporting emergent semantics. We
monstrate our approach on a large scale dataset stemming from an
line system.

@inproceedings{schmitz2006mining, author = {Schmitz, Christoph and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd}, title = {Mining Association Rules in Folksonomies}, editor = {Batagelj, V. and Bock, H.-H. and Ferligoj, A. and Žiberna, A.}, booktitle = {Data Science and Classification. Proceedings of the 10th IFCS Conf.}, series = {Studies in Classification, Data Analysis, and Knowledge Organization}, publisher = {Springer}, address = {Heidelberg}, year = {2006}, pages = {261--270}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/schmitz2006mining.pdf}, keywords = {2006, analysis, fca, folksonomies, folksonomy, l3s, myown, nepomuk, network, semantic}, abstract = {Social bookmark tools are rapidly emerging on the Web. In such
stems users are setting up lightweight conceptual structures
lled folksonomies. These systems provide currently relatively few
ructure. We discuss in this paper, how association rule mining
n be adopted to analyze and structure folksonomies, and how the results can be used
r ontology learning and supporting emergent semantics. We
monstrate our approach on a large scale dataset stemming from an
line system.} }

%0 = inproceedings %A = Schmitz, Christoph and Hotho, Andreas and Jäschke, Robert and Stumme, Gerd %B = Data Science and Classification. Proceedings of the 10th IFCS Conf. %C = Heidelberg %D = 2006 %I = Springer %T = Mining Association Rules in Folksonomies %U = http://www.kde.cs.uni-kassel.de/stumme/papers/2006/schmitz2006mining.pdf

@inproceedings{calders02mining, author = {Calders, Toon and Goethals, Bart}, title = {Mining All Non-derivable Frequent Itemsets}, booktitle = {PKDD '02: Proceedings of the 6th European Conference on Principles
of Data Mining and Knowledge Discovery}, publisher = {Springer-Verlag}, address = {London, UK}, year = {2002}, pages = {74--85}, isbn = {3-540-44037-2}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Calders, Toon and Goethals, Bart %B = PKDD '02: Proceedings of the 6th European Conference on Principles
of Data Mining and Knowledge Discovery %C = London, UK %D = 2002 %I = Springer-Verlag %T = Mining All Non-derivable Frequent Itemsets

@inproceedings{Kamber97metarule, author = {Kamber, M. and Han, J. and Chiang, Y.}, title = {Metarule-guided mining of multi-dimensional association rules using
data cubes.}, booktitle = {Proc. of the 3rd KDD Int'l Conf.}, year = {1997}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Kamber, M. and Han, J. and Chiang, Y. %B = Proc. of the 3rd KDD Int'l Conf. %D = 1997 %T = Metarule-guided mining of multi-dimensional association rules using
data cubes.

@book{hentig74magier, author = {von Hentig, Hartmut}, title = {Magier oder Magister? �ber die Einheit der Wissenschaft im Verst�ndigungsprozess}, publisher = {Suhrkamp}, address = {Frankfurt}, year = {1974}, keywords = {FCA, OntologyHandbook, fca, magier, magister, wissenscharft} }

%0 = book %A = von Hentig, Hartmut %C = Frankfurt %D = 1974 %I = Suhrkamp %T = Magier oder Magister? �ber die Einheit der Wissenschaft im Verst�ndigungsprozess

@inproceedings{burdick01mafia, author = {Burdick, D. and Calimlim, M. and Gehrke, J.}, title = {MAFIA: A maximal frequent itemset algorithm for transactional databases}, booktitle = {Proc. of the 17th Int. Conf. on Data Engineering}, publisher = {IEEE Computer Society}, year = {2001}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Burdick, D. and Calimlim, M. and Gehrke, J. %B = Proc. of the 17th Int. Conf. on Data Engineering %D = 2001 %I = IEEE Computer Society %T = MAFIA: A maximal frequent itemset algorithm for transactional databases

@inproceedings{GrohWille00Lattices, author = {Groh, B. and Wille, R.}, title = {Lattices of Triadic Concept Graphs}, editor = {Ganter, B. and Mineau, G. W.}, booktitle = {Conceptual Structures: Logical, Linguistic, and Computational Issues}, series = {Lecture Notes in Computer Science}, publisher = {Springer}, year = {2000}, volume = {1867}, pages = {332-341}, isbn = {3-540-67859-X}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Groh, B. and Wille, R. %B = Conceptual Structures: Logical, Linguistic, and Computational Issues %D = 2000 %I = Springer %T = Lattices of Triadic Concept Graphs

@book{lamport86latex, author = {Lamport, Leslie}, title = {LaTeX: A Document Preparation System}, publisher = {Addison-Wesley}, year = {1986}, keywords = {FCA, OntologyHandbook, document, lamport, latex, system, typesetting} }

%0 = book %A = Lamport, Leslie %D = 1986 %I = Addison-Wesley %T = LaTeX: A Document Preparation System

@inproceedings{Feldman95, author = {Feldman, R. and Dagan, I.}, title = {Knowledge discovery in textual databases}, booktitle = {Proceedings of the 1st international conference on Knowledge Discovery
and Data mining (KDD'95)}, publisher = {AAAI Press}, year = {1995}, pages = {112--117}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Feldman, R. and Dagan, I. %B = Proceedings of the 1st international conference on Knowledge Discovery
and Data mining (KDD'95) %D = 1995 %I = AAAI Press %T = Knowledge discovery in textual databases

@inproceedings{Han92, author = {Han, J. and Cai, Y. and Cercone, N.}, title = {Knowledge discovery in databases : An attribute oriented approach}, booktitle = {Proceedings of the 18th international conference on Very Large Data
Bases (VLDB'92)}, publisher = {Morgan Kaufmann}, year = {1992}, pages = {547--559}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Han, J. and Cai, Y. and Cercone, N. %B = Proceedings of the 18th international conference on Very Large Data
Bases (VLDB'92) %D = 1992 %I = Morgan Kaufmann %T = Knowledge discovery in databases : An attribute oriented approach

@inproceedings{Haetoenen96, author = {H�t�nen, K. and Klemettinen, M. and Mannila, H. and Ronkainen, P. and Toivonen, H.}, title = {Knowledge discovery from telecommunication network alarm databases}, booktitle = {Proceedings of the 12th International Conference on Data Engineering
(ICDE'96)}, publisher = {IEEE Computer Society Press}, year = {1996}, pages = {115--122}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = H�t�nen, K. and Klemettinen, M. and Mannila, H. and Ronkainen, P. and Toivonen, H. %B = Proceedings of the 12th International Conference on Data Engineering
(ICDE'96) %D = 1996 %I = IEEE Computer Society Press %T = Knowledge discovery from telecommunication network alarm databases

@inproceedings{Fayyad96b, author = {Fayyad, U. M. and Piatetsky-Shapiro, G. and Smyth, P.}, title = {Knowledge discovery and data mining : Towards a unifying framework}, booktitle = {Proceedings of the 2nd international conference on Knowledge Discovery
and Data mining (KDD'96)}, publisher = {AAAI Press}, year = {1996}, pages = {82--88}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Fayyad, U. M. and Piatetsky-Shapiro, G. and Smyth, P. %B = Proceedings of the 2nd international conference on Knowledge Discovery
and Data mining (KDD'96) %D = 1996 %I = AAAI Press %T = Knowledge discovery and data mining : Towards a unifying framework

@article{Fisher87, author = {Fisher, D. H.}, title = {Knowledge acquisition via incremental conceptual clustering}, editor = {Holte, R. C.}, journal = {Machine Learning}, publisher = {Kluwer Academic Publishers}, year = {1987}, volume = {2}, number = {2}, pages = {139--172}, keywords = {FCA, OntologyHandbook} }

%0 = article %A = Fisher, D. H. %D = 1987 %I = Kluwer Academic Publishers %T = Knowledge acquisition via incremental conceptual clustering

@misc{BSI03ITBaseline, author = {German Federal Office for Information Security}, title = {IT Baseline Protection Manual}, year = {2003}, keywords = {FCA, OntologyHandbook} }

%0 = misc %A = German Federal Office for Information Security %B = } %C = %D = 2003 %I = %T = IT Baseline Protection Manual} %U =

@inproceedings{hotho2006information, author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd}, title = {Information Retrieval in Folksonomies: Search and Ranking}, booktitle = {Proceedings of the 3rd European Semantic Web Conference}, series = {Lecture Notes in Computer Science}, publisher = {Springer}, year = {2006}, pages = {411-426}, keywords = {FCA, OntologyHandbook, folkrank, folksonomy, graph, information, mining, pagerank, rank, ranking, retrieval, search, seminar2006} }

%0 = inproceedings %A = Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd %B = Proceedings of the 3rd European Semantic Web Conference %D = 2006 %I = Springer %T = Information Retrieval in Folksonomies: Search and Ranking

@article{Godin95, author = {Godin, R. and Missaoui, R. and Alaoui, H.}, title = {Incremental concept formation algorithms based on Galois
(concept) lattices}, editor = {Cercone, N. and McCalla, G.}, journal = {Computational Intelligence}, publisher = {Blackwell Publishers}, year = {1995}, volume = {11}, number = {2}, pages = {246-267}, keywords = {FCA, OntologyHandbook} }

%0 = article %A = Godin, R. and Missaoui, R. and Alaoui, H. %D = 1995 %I = Blackwell Publishers %T = Incremental concept formation algorithms based on Galois
(concept) lattices

@inproceedings{Harinarayan96, author = {Harinarayan, V. and Rajaraman, A. and Ullman, J. D.}, title = {Implementing data cubes efficiently}, booktitle = {Proceedings of the 1996 ACM SIGMOD international conference on Management
of Data (SIGMOD'96)}, publisher = {ACM Press}, year = {1996}, pages = {205--216}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Harinarayan, V. and Rajaraman, A. and Ullman, J. D. %B = Proceedings of the 1996 ACM SIGMOD international conference on Management
of Data (SIGMOD'96) %D = 1996 %I = ACM Press %T = Implementing data cubes efficiently

@inproceedings{stumme2004iceberg, author = {Stumme, Gerd}, title = {Iceberg Query Lattices for Datalog}, editor = {Wolff, Karl Erich and Pfeiffer, Heather D. and Delugach, Harry S.}, booktitle = {Conceptual Structures at Work: 12th International Conference on Conceptual Structures (ICCS 2004)}, series = {LNCS}, publisher = {Springer}, address = {Heidelberg}, year = {2004}, volume = {3127}, pages = {109-125}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2004/stumme2004iceberg.pdf}, keywords = {2004, analysis, concept, context, datalog, families, family, fca, formal, iceberg, itegpub, l3s, lattices, myown, pcf, power, queries, query} }

%0 = inproceedings %A = Stumme, Gerd %B = Conceptual Structures at Work: 12th International Conference on Conceptual Structures (ICCS 2004) %C = Heidelberg %D = 2004 %I = Springer %T = Iceberg Query Lattices for Datalog %U = http://www.kde.cs.uni-kassel.de/stumme/papers/2004/stumme2004iceberg.pdf

@inproceedings{Han97, author = {Han, J. and Koperski, K. and Stefanovic, N.}, title = {GeoMiner : A system prototype for spatial data mining}, booktitle = {Proceedings of the 1997 ACM SIGMOD international conference on Management
of Data (SIGMOD'97)}, publisher = {ACM Press}, year = {1997}, pages = {553--556}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Han, J. and Koperski, K. and Stefanovic, N. %B = Proceedings of the 1997 ACM SIGMOD international conference on Management
of Data (SIGMOD'97) %D = 1997 %I = ACM Press %T = GeoMiner : A system prototype for spatial data mining

@incollection{Fayyad96c, author = {Fayyad, U. M. and Piatetsky-Shapiro, G. and Smyth, P.}, title = {From data mining to knowledge discovery : An overview}, editor = {Fayyad, U. M. and Piatetsky-Shapiro, G. and Smyth, P. and Uthurusamy, R.}, booktitle = {Advances in Knowledge Discovery and Data Mining}, publisher = {AAAI Press}, year = {1996}, pages = {1--30}, keywords = {FCA, OntologyHandbook} }

%0 = incollection %A = Fayyad, U. M. and Piatetsky-Shapiro, G. and Smyth, P. %B = Advances in Knowledge Discovery and Data Mining %D = 1996 %I = AAAI Press %T = From data mining to knowledge discovery : An overview

@book{Ganter99, author = {Ganter, B. and Wille, R.}, title = {Formal Concept Analysis: Mathematical foundations}, publisher = {Springer}, year = {1999}, keywords = {FCA, OntologyHandbook} }

%0 = book %A = Ganter, B. and Wille, R. %D = 1999 %I = Springer %T = Formal Concept Analysis: Mathematical foundations

@book{ganter99formal, author = {Ganter, B. and Wille, R.}, title = {Formal Concept Analysis: Mathematical Foundations}, publisher = {Springer}, year = {1999}, note = {Translation of: itFormale Begriffsanalyse: Mathematische
Grundlagen. Springer, Heidelberg 1996.}, keywords = {FCA, OntologyHandbook, analysis, concept, fca, formal, math} }

%0 = book %A = Ganter, B. and Wille, R. %D = 1999 %I = Springer %T = Formal Concept Analysis: Mathematical Foundations

@proceedings{ganter05formal,, title = {Formal Concept Analysis: Foundations and Applications}, editor = {Ganter, B. and Stumme, G. and Wille, R.}, series = {LNAI}, publisher = {Springer}, address = {Heidelberg}, year = {2005}, volume = {3626}, note = {http://www.informatik.uni-trier.de/~ley/db/conf/fca/fca2005.html}, url = {http://www.springerlink.com/content/978-3-540-27891-7/}, keywords = {2005, book, fca, l3s, myown} }

%0 = proceedings %B = } %C = Heidelberg %D = 2005 %I = Springer %T = Formal Concept Analysis: Foundations and Applications} %U = http://www.springerlink.com/content/978-3-540-27891-7/

@techreport{Burmeister98, author = {Burmeister, P.}, title = {Formal concept analysis with ConImp : Introduction to the
basic features}, address = {Darmstadt, Germany}, year = {1998}, note = {http://www.mathematik.tu-darmstadt.de/~burmeister/ConImpIntro.ps}, keywords = {FCA, OntologyHandbook} }

%0 = techreport %A = Burmeister, P. %B = } %C = Darmstadt, Germany %D = 1998 %I = %T = Formal concept analysis with ConImp : Introduction to the
basic features} %U =

@inproceedings{stumme02formalconcept, author = {Stumme, G.}, title = {Formal Concept Analysis on its Way from Mathematics to Computer Science}, editor = {Priss, U. and Corbett, D. and Angelova, G.}, booktitle = {Conceptual Structures: Integration and Interfaces }, series = {LNAI}, publisher = {Springer}, address = {Heidelberg}, year = {2002}, volume = {2393}, pages = {2-19}, note = {Invited Talk, summary of testumme03offtonew}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2002/ICCS02.pdf}, keywords = {2002, OntologyHandbook, analysis, computer, concept, fca, formal, informatik, mathematics, mathematik, myown, science} }

%0 = inproceedings %A = Stumme, G. %B = Conceptual Structures: Integration and Interfaces %C = Heidelberg %D = 2002 %I = Springer %T = Formal Concept Analysis on its Way from Mathematics to Computer Science %U = http://www.kde.cs.uni-kassel.de/stumme/papers/2002/ICCS02.pdf

@inproceedings{Klemettinen94, author = {Klemettinen, M. and Mannila, H. and Ronkainen, P. and Toivonen, H. and Verkamo, A. I.}, title = {Finding interesting rules from large sets of discovered association
rules}, booktitle = {Proceedings of the 3rd international Conference on Information and
Knowledge Management (CIKM'94)}, publisher = {ACM Press}, year = {1994}, pages = {401--407}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Klemettinen, M. and Mannila, H. and Ronkainen, P. and Toivonen, H. and Verkamo, A. I. %B = Proceedings of the 3rd international Conference on Information and
Knowledge Management (CIKM'94) %D = 1994 %I = ACM Press %T = Finding interesting rules from large sets of discovered association
rules

@article{Ganter91, author = {Ganter, B. and Reuter, K.}, title = {Finding all closed sets : A general approach}, journal = {Order}, publisher = {Kluwer Academic Publishers}, year = {1991}, volume = {8}, pages = {283-290}, keywords = {FCA, OntologyHandbook} }

%0 = article %A = Ganter, B. and Reuter, K. %D = 1991 %I = Kluwer Academic Publishers %T = Finding all closed sets : A general approach

@phdthesis{Lin98b, author = {Lin, D.}, title = {Fast algorithms for discovering the maximum frequent sets}, school = {University of New York}, year = {1998}, keywords = {FCA, OntologyHandbook} }

%0 = phdthesis %A = Lin, D. %D = 1998 %T = Fast algorithms for discovering the maximum frequent sets

@incollection{Han96a, author = {Han, J. and Fu, Y.}, title = {Exploration of the power of attribute oriented induction in data
mining}, editor = {Fayyad, U. M. and Piatetsky-Shapiro, G. and Smyth, P. and Uthurusamy, R.}, booktitle = {Advances in Knowledge Discovery and Data Mining}, publisher = {AAAI Press}, year = {1996}, pages = {399--421}, keywords = {FCA, OntologyHandbook} }

%0 = incollection %A = Han, J. and Fu, Y. %B = Advances in Knowledge Discovery and Data Mining %D = 1996 %I = AAAI Press %T = Exploration of the power of attribute oriented induction in data
mining

@phdthesis{John97, author = {John, G. H.}, title = {Enhancements to the data mining process}, school = {University of Stanford}, year = {1997}, keywords = {FCA, OntologyHandbook} }

%0 = phdthesis %A = John, G. H. %D = 1997 %T = Enhancements to the data mining process

@inproceedings{Fayet98, author = {Fayet, A. and Giacometti, A. and Laurent, D. and Spyratos, N.}, title = {Découverte de r�gles pertinentes dans les bases de donn�es}, booktitle = {Actes des 14�mes journ�es Bases de Donn�es Avanc�es (BDA'98)}, year = {1998}, pages = {197--211}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Fayet, A. and Giacometti, A. and Laurent, D. and Spyratos, N. %B = Actes des 14�mes journ�es Bases de Donn�es Avanc�es (BDA'98) %D = 1998 %T = Découverte de r�gles pertinentes dans les bases de donn�es

@inproceedings{Brin97a, author = {Brin, S. and Motwani, R. and Ullman, J. D. and Tsur, S.}, title = {Dynamic itemset counting and implication rules for market basket
data}, booktitle = {Proceedings of the 1997 ACM SIGMOD international conference on Management
of Data (SIGMOD'97)}, publisher = {ACM Press}, year = {1997}, pages = {255--264}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Brin, S. and Motwani, R. and Ullman, J. D. and Tsur, S. %B = Proceedings of the 1997 ACM SIGMOD international conference on Management
of Data (SIGMOD'97) %D = 1997 %I = ACM Press %T = Dynamic itemset counting and implication rules for market basket
data

This paper discusses an document discovery tool based on
nceptual clustering by formal concept analysis. The program
lows users to navigate email using a visual lattice metaphor
ther than a tree. It implements a virtual file structure over
ail where files and entire directories can appear in multiple
sitions. The content and shape of the lattice formed by the
nceptual ontology can assist in email discovery. The system
scribed provides more flexibility in retrieving stored emails
an what is normally available in email clients. The paper
scusses how conceptual ontologies can leverage traditional
cument retrieval systems and aid knowledge discovery in document
llections.

@article{cole03document, author = {Cole, Richard J. and Eklund, Peter W. and Stumme, Gerd}, title = {Document Retrieval for Email Search and Discovery using Formal Concept Analysis}, journal = {Journal of Applied Artificial Intelligence (AAI)}, year = {2003}, volume = {17}, number = {3}, pages = {257-280}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2003/AAI03_emails.pdf}, keywords = {2003, analysis, concept, email, fca, formal, information, myown, nepomuk, retrieval, search}, abstract = {This paper discusses an document discovery tool based on conceptual clustering by formal concept analysis. The program allows users to navigate email using a visual lattice metaphor rather than a tree. It implements a virtual file structure over email where files and entire directories can appear in multiple positions. The content and shape of the lattice formed by the conceptual ontology can assist in email discovery. The system described provides more flexibility in retrieving stored emails than what is normally available in email clients. The paper discusses how conceptual ontologies can leverage traditional document retrieval systems and aid knowledge discovery in document collections.} }

%0 = article %A = Cole, Richard J. and Eklund, Peter W. and Stumme, Gerd %D = 2003 %T = Document Retrieval for Email Search and Discovery using Formal Concept Analysis %U = http://www.kde.cs.uni-kassel.de/stumme/papers/2003/AAI03_emails.pdf

@inproceedings{Koperski95, author = {Koperski, K. and Han, J.}, title = {Discovery of spatial association rules in geographic information
databases}, booktitle = {Proceedings of the 4th international Symposium on advances in Spatial
Databases (SSD'95)}, series = {Lecture Notes in Computer Science, Vol. 951}, publisher = {Springer-Verlag}, year = {1995}, pages = {47--66}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Koperski, K. and Han, J. %B = Proceedings of the 4th international Symposium on advances in Spatial
Databases (SSD'95) %D = 1995 %I = Springer-Verlag %T = Discovery of spatial association rules in geographic information
databases

@inproceedings{Han95, author = {Han, J. and Fu, Y.}, title = {Discovery of multiple-level association rules from large databases}, booktitle = {Proceedings of the 21st international conference on Very Large Data
Bases (VLDB'95)}, publisher = {Morgan Kaufmann}, year = {1995}, pages = {420--431}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Han, J. and Fu, Y. %B = Proceedings of the 21st international conference on Very Large Data
Bases (VLDB'95) %D = 1995 %I = Morgan Kaufmann %T = Discovery of multiple-level association rules from large databases

@inproceedings{Lent97, author = {Lent, B. and Agrawal, R. and Srikant, R.}, title = {Discovering trends in text databases}, booktitle = {Proceedings of the 3rd international conference on Knowledge Discovery
and Data mining (KDD'97)}, publisher = {AAAI Press}, year = {1997}, pages = {227--230}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Lent, B. and Agrawal, R. and Srikant, R. %B = Proceedings of the 3rd international conference on Knowledge Discovery
and Data mining (KDD'97) %D = 1997 %I = AAAI Press %T = Discovering trends in text databases

@article{jaeschke08discovering, author = {Jäschke, Robert and Hotho, Andreas and Schmitz, Christoph and Ganter, Bernhard and Stumme, Gerd}, title = {Discovering Shared Conceptualizations in Folksonomies}, journal = {Journal of Web Semantics}, year = {2008}, volume = {6}, number = {1}, pages = {38-53}, url = {http://dx.doi.org/10.1016/j.websem.2007.11.004}, keywords = {2008, FCA, OntologyHandbook, analysis, bibsonomy, concept, discovering, fca, folksonomies, formal, itegpub, l3s, myown, shared, triadic} }

%0 = article %A = Jäschke, Robert and Hotho, Andreas and Schmitz, Christoph and Ganter, Bernhard and Stumme, Gerd %D = 2008 %T = Discovering Shared Conceptualizations in Folksonomies %U = http://dx.doi.org/10.1016/j.websem.2007.11.004

@inproceedings{Gunopulos97b, author = {Gunopulos, D. and Mannila, H. and Saluja, S.}, title = {Discovering all most specific sentences by randomized algorithms}, booktitle = {Proceedings of the 6th biennial International Conference on Database
Theory (ICDT'97)}, series = {Lecture Notes in Computer Science, Vol. 1186}, publisher = {Springer-Verlag}, year = {1997}, pages = {215-229}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Gunopulos, D. and Mannila, H. and Saluja, S. %B = Proceedings of the 6th biennial International Conference on Database
Theory (ICDT'97) %D = 1997 %I = Springer-Verlag %T = Discovering all most specific sentences by randomized algorithms

@article{Godin98design, author = {Godin, R. and Mili, H. and Mineau, G. and Missaoui, R. and Arfi, A. and Chau, T.}, title = {Design of class hierarchies based on concept (Galois) lattices.}, journal = {TAPOS}, year = {1998}, volume = {4}, number = {2}, pages = {117--134}, keywords = {FCA, OntologyHandbook} }

%0 = article %A = Godin, R. and Mili, H. and Mineau, G. and Missaoui, R. and Arfi, A. and Chau, T. %D = 1998 %T = Design of class hierarchies based on concept (Galois) lattices.

@inproceedings{Han96b, author = {Han, J. and Fu, Y. and Wang, W. and Chiang, J. and Gong, W. and Koperski, K. and Li, D. and Lu, Y. and Rajan, A. and Stefanovic, N. and Xia, B. and Zaïane, O. R.}, title = {DBMiner : A system for mining knowledge in large relational
databases}, booktitle = {Proceedings of the 2nd international conference on Knowledge Discovery
and Data mining (KDD'96)}, publisher = {AAAI Press}, year = {1996}, pages = {250--255}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Han, J. and Fu, Y. and Wang, W. and Chiang, J. and Gong, W. and Koperski, K. and Li, D. and Lu, Y. and Rajan, A. and Stefanovic, N. and Xia, B. and Zaïane, O. R. %B = Proceedings of the 2nd international conference on Knowledge Discovery
and Data mining (KDD'96) %D = 1996 %I = AAAI Press %T = DBMiner : A system for mining knowledge in large relational
databases

@inproceedings{Han97b, author = {Han, J. and Chiang, J. and Chee, S. and Chen, J. and Chen, Q. and Cheng, S. and Gong, W. and Kamber, M. and Liu, K. Koperski G. and Lu, Y. and and N. Stefanovic and Winstone, L. and Xia, B. and Zaïane, O. R. and Zhang, S. and Zhu, H.}, title = {DBMiner : A system for data mining in relational databases
and data warehouses}, booktitle = {Proceedings of the 1997 GASCON metting of minds (GASCON'97)}, year = {1997}, pages = {249--260}, note = {ftp://ftp.fas.sfu.ca/pub/cs/han/kdd/cascon97.ps}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Han, J. and Chiang, J. and Chee, S. and Chen, J. and Chen, Q. and Cheng, S. and Gong, W. and Kamber, M. and Liu, K. Koperski G. and Lu, Y. and and N. Stefanovic and Winstone, L. and Xia, B. and Zaïane, O. R. and Zhang, S. and Zhu, H. %B = Proceedings of the 1997 GASCON metting of minds (GASCON'97) %D = 1997 %T = DBMiner : A system for data mining in relational databases
and data warehouses

@book{Han02data, author = {Han, J. and Kamber, M.}, title = {Data: Mining: Concepts and Techniques}, publisher = {Morgan Kaufmann}, year = {2002}, keywords = {FCA, OntologyHandbook} }

%0 = book %A = Han, J. and Kamber, M. %D = 2002 %I = Morgan Kaufmann %T = Data: Mining: Concepts and Techniques

@article{Han93, author = {Han, J. and Cai, Y. and Cercone, N.}, title = {Data-driven discovery of quantitative rules in relational databases}, journal = {IEEE Transansaction on Knowledge and Data Engineering}, publisher = {IEEE Computer Society Press}, year = {1993}, volume = {5}, number = {1}, pages = {29--40}, keywords = {FCA, OntologyHandbook} }

%0 = article %A = Han, J. and Cai, Y. and Cercone, N. %D = 1993 %I = IEEE Computer Society Press %T = Data-driven discovery of quantitative rules in relational databases

@book{Han:book00, author = {Han, J. and Kamber, M.}, title = {Data Mining: Concepts and Techniques}, publisher = {Morgan Kaufmann}, year = {2000}, keywords = {FCA, OntologyHandbook} }

%0 = book %A = Han, J. and Kamber, M. %D = 2000 %I = Morgan Kaufmann %T = Data Mining: Concepts and Techniques

@phdthesis{Bastide00, author = {Bastide, Y.}, title = {Data Mining: algorithmes par niveau, techniques d'implementation
et applications}, school = {Université de Clermont-Ferrand II}, year = {2000}, keywords = {FCA, OntologyHandbook} }

%0 = phdthesis %A = Bastide, Y. %D = 2000 %T = Data Mining: algorithmes par niveau, techniques d'implementation
et applications

@inproceedings{Gunopulos97a, author = {Gunopulos, D. and Khardon, R. and Mannila, H. and Toivonen, H.}, title = {Data mining, hypergraph transversals, and machine learning}, booktitle = {Proceedings of the 16th ACM SIGACT-SIGMOD-SIGART symposium on Principles
of Database Systems (PODS'97)}, publisher = {ACM Press}, year = {1997}, pages = {209--216}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Gunopulos, D. and Khardon, R. and Mannila, H. and Toivonen, H. %B = Proceedings of the 16th ACM SIGACT-SIGMOD-SIGART symposium on Principles
of Database Systems (PODS'97) %D = 1997 %I = ACM Press %T = Data mining, hypergraph transversals, and machine learning

We provide a new method for systematically structuring the top-down level of ontologies.
is based on an interactive, top-down knowledge acquisition
ocess, which assures that the knowledge engineer
nsiders all possible cases while avoiding redundant acquisition.
e method is suited especially for creating/merging the top
rt(s) of the ontologies, where high accuracy is required, and for supporting the merging of two (or more) ontologies on that level.

@inproceedings{ganter03creation, author = {Ganter, Bernhard and Stumme, Gerd}, title = {Creation and Merging of Ontology Top-Levels}, editor = {de Moor, Aldo and Lex, Wilfried and Ganter, Bernhard}, booktitle = {Conceptual Structures for Knowledge Creation and Communication.}, series = {LNAI}, publisher = {Springer}, address = {Heidelberg}, year = {2003}, volume = {2746}, pages = {131-145}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2003/ganter2003creation.pdf}, keywords = {2003, analysis, concept, fca, formal, merging, myown, ontologies, ontology}, abstract = {We provide a new method for systematically structuring the top-down level of ontologies.
is based on an interactive, top--down knowledge acquisition
ocess, which assures that the knowledge engineer
nsiders all possible cases while avoiding redundant acquisition.
e method is suited especially for creating/merging the top
rt(s) of the ontologies, where high accuracy is required, and for supporting the merging of two (or more) ontologies on that level.} }

%0 = inproceedings %A = Ganter, Bernhard and Stumme, Gerd %B = Conceptual Structures for Knowledge Creation and Communication. %C = Heidelberg %D = 2003 %I = Springer %T = Creation and Merging of Ontology Top-Levels %U = http://www.kde.cs.uni-kassel.de/stumme/papers/2003/ganter2003creation.pdf

@article{kent95creating, author = {Kent, Robert E. and Neuss, Christian}, title = {Creating a Web Analysis and Visualization Environment}, journal = {Computer Networks and ISDN Systems}, year = {1995}, volume = {28}, number = {1&}, pages = {109-117}, url = {http://dblp.uni-trier.de/db/journals/cn/cn28.html#KentN95}, keywords = {Analysis, Creating, FCA, OntologyHandbook, Visualization, Web, analysis, concept, creating, fca, formal, visualization, web} }

%0 = article %A = Kent, Robert E. and Neuss, Christian %D = 1995 %T = Creating a Web Analysis and Visualization Environment %U = http://dblp.uni-trier.de/db/journals/cn/cn28.html#KentN95

@proceedings{dau05contributions,, title = {Contributions to ICCS 2005}, editor = {Dau, Frithjof and Mugnier, Marie-Laure and Stumme, Gerd}, booktitle = {Contributions to ICCS 2005}, publisher = {kassel university press}, address = {Kassel}, year = {2005}, url = {http://www.kde.cs.uni-kassel.de/conf/iccs05}, isbn = {3-89958-138-5}, keywords = {2005, Germany, Kassel, analysis, concept, conceptual, conference, fca, formal, graphs, iccs, knowledge, l3s, myown, proceedings, sharing, structures} }

%0 = proceedings %B = Contributions to ICCS 2005} %C = Kassel %D = 2005 %I = kassel university press %T = Contributions to ICCS 2005} %U = http://www.kde.cs.uni-kassel.de/conf/iccs05

@inproceedings{kryszkiewicz01concise, author = {Kryszkiewicz, Marzena}, title = {Concise Representation of Frequent Patterns Based on Disjunction-Free
Generators}, booktitle = {ICDM '01: Proceedings of the 2001 IEEE International Conference on
Data Mining}, publisher = {IEEE Computer Society}, address = {Washington, DC, USA}, year = {2001}, pages = {305--312}, isbn = {0-7695-1119-8}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Kryszkiewicz, Marzena %B = ICDM '01: Proceedings of the 2001 IEEE International Conference on
Data Mining %C = Washington, DC, USA %D = 2001 %I = IEEE Computer Society %T = Concise Representation of Frequent Patterns Based on Disjunction-Free
Generators

@proceedings{conf/iccs/2005,, title = {Conceptual Structures: Common Semantics for Sharing Knowledge, 13th International Conference on Conceptual Structures, ICCS 2005, Kassel, Germany, July 17-22, 2005, Proceedings}, editor = {Dau, Frithjof and Mugnier, Marie-Laure and Stumme, Gerd}, booktitle = {ICCS}, series = {Lecture Notes in Computer Science}, publisher = {Springer}, year = {2005}, volume = {3596}, url = {http://www.kde.cs.uni-kassel.de/conf/iccs05}, isbn = {3-540-27783-8}, keywords = {2005, Germany, Kassel, analysis, concept, conceptual, conference, fca, formal, graphs, iccs, knowledge, l3s, myown, proceedings, sharing, structures} }

%0 = proceedings %B = ICCS} %C = %D = 2005 %I = Springer %T = Conceptual Structures: Common Semantics for Sharing Knowledge, 13th International Conference on Conceptual Structures, ICCS 2005, Kassel, Germany, July 17-22, 2005, Proceedings} %U = http://www.kde.cs.uni-kassel.de/conf/iccs05

@proceedings{delugach01conceptual,, title = {Conceptual Structures -- Broadening the Base. Proc. 9th International Conference on Conceptual Structures}, editor = {Delugach, H. and Stumme, G.}, series = {LNAI}, publisher = {Springer}, address = {Heidelberg}, year = {2001}, volume = {2120}, keywords = {2001, analysis, cg, cgs, concept, conceptual, fca, formal, graphs, iccs, myown, structures} }

%0 = proceedings %B = } %C = Heidelberg %D = 2001 %I = Springer %T = Conceptual Structures -- Broadening the Base. Proc. 9th International Conference on Conceptual Structures} %U =

Among many other knowledge representations formalisms, Ontologies
d Formal Concept Analysis (FCA) aim at modeling 'concepts'. We
scuss how these two formalisms may complement another from an
plication point of view. In particular, we will see how FCA can
used to support Ontology Engineering, and how ontologies can be
ploited in FCA applications. The interplay of FCA and ontologies
studied along the life cycle of an ontology:
i) FCA can support the building of the ontology as a
earning technique.
ii) The established ontology can be analyzed and navigated by
sing techniques of FCA.
iii) Last but not least, the ontology may be used to improve an FCA
pplication.

@inproceedings{cimiano2004concept, author = {Cimiano, Philipp and Hotho, Andreas and Stumme, Gerd and Tane, Julien}, title = {Conceptual Knowledge Processing with Formal Concept Analysis and Ontologies}, editor = {Eklund, Peter}, booktitle = {Concept Lattices}, series = {LNAI}, publisher = {Springer}, address = {Heidelberg}, year = {2004}, volume = {2961}, pages = {189-207}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2004/cimiano2004concept.pdf}, isbn = {3-540-23258-3}, keywords = {2004, ckp, conceptual, fca, itegpub, knowledge, l3s, myown, ontologies, processing}, abstract = {Among many other knowledge representations formalisms, Ontologies
d Formal Concept Analysis (FCA) aim at modeling 'concepts'. We
scuss how these two formalisms may complement another from an
plication point of view. In particular, we will see how FCA can
used to support Ontology Engineering, and how ontologies can be
ploited in FCA applications. The interplay of FCA and ontologies
studied along the life cycle of an ontology:
i) FCA can support the building of the ontology as a
earning technique.
ii) The established ontology can be analyzed and navigated by
sing techniques of FCA.
iii) Last but not least, the ontology may be used to improve an FCA
pplication.} }

%0 = inproceedings %A = Cimiano, Philipp and Hotho, Andreas and Stumme, Gerd and Tane, Julien %B = Concept Lattices %C = Heidelberg %D = 2004 %I = Springer %T = Conceptual Knowledge Processing with Formal Concept Analysis and Ontologies %U = http://www.kde.cs.uni-kassel.de/stumme/papers/2004/cimiano2004concept.pdf

@incollection{cimiano2004conceptual, author = {Cimiano, Philipp and Hotho, Andreas and Stumme, Gerd and Tane, Julien}, title = {Conceptual Knowledge Processing with Formal Concept
Analysis and Ontologies}, editor = {Eklund, Peter}, booktitle = {Concept Lattices}, series = {Lecture Notes in Computer Science}, publisher = {Springer}, address = {Berlin/Heidelberg}, year = {2004}, volume = {2961}, pages = {189--207}, url = {http://dx.doi.org/10.1007/978-3-540-24651-0_18}, isbn = {978-3-540-21043-6}, keywords = {2004, citedBy:doerfel2012publication, fca, icfca, itegpub, knowledge, l3s, myown, processing} }

%0 = incollection %A = Cimiano, Philipp and Hotho, Andreas and Stumme, Gerd and Tane, Julien %B = Concept Lattices %C = Berlin/Heidelberg %D = 2004 %I = Springer %T = Conceptual Knowledge Processing with Formal Concept
Analysis and Ontologies %U = http://dx.doi.org/10.1007/978-3-540-24651-0_18

In this paper we discuss Conceptual Knowledge Discovery in Databases (CKDD) as it is developing in the field of Conceptual Knowledge
rocessing. Conceptual Knowledge
rocessing is based on the mathematical theory of Formal Concept
nalysis which has become a successful theory for data analysis during
he last two decades. CKDD aims to support a human-centered process
discovering knowledge from data by visualizing and analyzing
e conceptual structure of the data. We dicuss how the
nagement system TOSCANA for conceptual information systems
pports CKDD, and illustrate it by two applications in database
rketing and flight movement analysis. Finally, we present a
w tool for conceptual deviation discovery, Chianti.

@article{hereth03conceptual, author = {Hereth, Joachim and Stumme, Gerd and Wille, Rudolf and Wille, Uta}, title = {Conceptual Knowledge Discovery - a Human-Centered Approach}, journal = {Journal of Applied Artificial Intelligence (AAI)}, year = {2003}, volume = {17}, number = {3}, pages = {281-301}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2003/hereth2003conceptual.pdf}, keywords = {2003, analysis, concept, conceptual, discovery, fca, formal, human, kdd, knowledge, myown}, abstract = {In this paper we discuss Conceptual Knowledge Discovery in Databases (CKDD) as it is developing in the field of Conceptual Knowledge Processing. Conceptual Knowledge Processing is based on the mathematical theory of Formal Concept Analysis which has become a successful theory for data analysis during the last two decades. CKDD aims to support a human-centered process of discovering knowledge from data by visualizing and analyzing the conceptual structure of the data. We dicuss how the management system TOSCANA for conceptual information systems supports CKDD, and illustrate it by two applications in database marketing and flight movement analysis. Finally, we present a new tool for conceptual deviation discovery, Chianti.} }

%0 = article %A = Hereth, Joachim and Stumme, Gerd and Wille, Rudolf and Wille, Uta %D = 2003 %T = Conceptual Knowledge Discovery - a Human-Centered Approach %U = http://www.kde.cs.uni-kassel.de/stumme/papers/2003/hereth2003conceptual.pdf

@inproceedings{becker00conceptual, author = {Becker, K. and Stumme, G. and Wille, R. and Wille, U. and Zickwolff, M.}, title = {Conceptual Information Systems Discussed Through an IT-Security Tool}, editor = {Dieng, R. and Corby, O.}, booktitle = {Knowledge Engineering and Knowledge Management. Methods, Models, and Tools.}, series = {LNAI}, publisher = {Springer}, address = {Heidelberg}, year = {2000}, volume = {1937}, pages = {352-365}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2000/EKAW00.pdf}, keywords = {2000, OntologyHandbook, analysis, concept, conceptual, fca, formal, information, it, lattices, myown, security, system, systems, triadic} }

%0 = inproceedings %A = Becker, K. and Stumme, G. and Wille, R. and Wille, U. and Zickwolff, M. %B = Knowledge Engineering and Knowledge Management. Methods, Models, and Tools. %C = Heidelberg %D = 2000 %I = Springer %T = Conceptual Information Systems Discussed Through an IT-Security Tool %U = http://www.kde.cs.uni-kassel.de/stumme/papers/2000/EKAW00.pdf

We introduce the notion of iceberg concept lattices
and show their use in knowledge discovery in
databases. Iceberg lattices are a conceptual
clustering method, which is well suited for analyzing
very large databases. They also serve as a condensed
representation of frequent itemsets, as starting
point for computing bases of association rules, and
as a visualization method for association rules.
Iceberg concept lattices are based on the theory of
Formal Concept Analysis, a mathematical theory with
applications in data analysis, information retrieval,
and knowledge discovery. We present a new algorithm
called TITANIC for computing (iceberg) concept
lattices. It is based on data mining techniques with
a level-wise approach. In fact, TITANIC can be used
for a more general problem: Computing arbitrary
closure systems when the closure operator comes along
with a so-called weight function. The use of weight
functions for computing closure systems has not been
discussed in the literature up to now. Applications
providing such a weight function include association
rule mining, functional dependencies in databases,
conceptual clustering, and ontology engineering. The
algorithm is experimentally evaluated and compared
with Ganter's Next-Closure algorithm. The evaluation
shows an important gain in efficiency, especially for
weakly correlated data.

@article{stumme2002computing, author = {Stumme, Gerd and Taouil, Rafik and Bastide, Yves and Pasquier, Nicolas and Lakhal, Lotfi}, title = {Computing iceberg concept lattices with TITANIC}, journal = {Data & Knowledge Engineering}, publisher = {Elsevier Science Publishers B. V.}, address = {Amsterdam, The Netherlands, The Netherlands}, year = {2002}, volume = {42}, number = {2}, pages = {189--222}, url = {http://portal.acm.org/citation.cfm?id=606457}, doi = {10.1016/S0169-023X(02)00057-5}, issn = {0169-023X}, keywords = {citedBy:doerfel2012publication, fca, icfca, itegpub, l3s, myown, titanic}, abstract = {We introduce the notion of iceberg concept lattices and show their use in knowledge discovery in databases. Iceberg lattices are a conceptual clustering method, which is well suited for analyzing very large databases. They also serve as a condensed representation of frequent itemsets, as starting point for computing bases of association rules, and as a visualization method for association rules. Iceberg concept lattices are based on the theory of Formal Concept Analysis, a mathematical theory with applications in data analysis, information retrieval, and knowledge discovery. We present a new algorithm called TITANIC for computing (iceberg) concept lattices. It is based on data mining techniques with a level-wise approach. In fact, TITANIC can be used for a more general problem: Computing arbitrary closure systems when the closure operator comes along with a so-called weight function. The use of weight functions for computing closure systems has not been discussed in the literature up to now. Applications providing such a weight function include association rule mining, functional dependencies in databases, conceptual clustering, and ontology engineering. The algorithm is experimentally evaluated and compared with Ganter's Next-Closure algorithm. The evaluation shows an important gain in efficiency, especially for weakly correlated data.} }

%0 = article %A = Stumme, Gerd and Taouil, Rafik and Bastide, Yves and Pasquier, Nicolas and Lakhal, Lotfi %C = Amsterdam, The Netherlands, The Netherlands %D = 2002 %I = Elsevier Science Publishers B. V. %T = Computing iceberg concept lattices with TITANIC %U = http://portal.acm.org/citation.cfm?id=606457

@article{kuznetsov02comparing, author = {Kuznetsov, S. and Obiedkov, S.}, title = {Comparing performance of algorithms for generating concept lattices}, journal = {Journal of Experimental and Theoretical Artificial Intelligence}, year = {2002}, volume = {14}, pages = {189-216}, url = {/brokenurl#citeseer.ist.psu.edu/666686.html}, keywords = {FCA, OntologyHandbook, algorithm, algorithms, analysis, concept, fca, formal} }

%0 = article %A = Kuznetsov, S. and Obiedkov, S. %D = 2002 %T = Comparing performance of algorithms for generating concept lattices %U = /brokenurl#citeseer.ist.psu.edu/666686.html

We describe online collaborative communities by tripartite networks,
the nodes being persons, items and tags. We introduce projection
methods in order to uncover the structures of the networks, i.e.
communities of users, genre families... <br />To do so, we focus
on the correlations between the nodes, depending on their profiles,
and use percolation techniques that consist in removing less correlated
links and observing the shaping of disconnected islands. The structuring
of the network is visualised by using a tree representation. The
notion of diversity in the system is also discussed.

@misc{citeulike:484851, author = {Lambiotte, R. and Ausloos, M.}, title = {Collaborative tagging as a tripartite network}, year = {2005}, note = {ttarXiv:cs.DS/0512090}, url = {http://arxiv.org/abs/cs.DS/0512090}, keywords = {FCA, OntologyHandbook, collaboration, discovery, folksonomy, tagging, taxonomy}, abstract = {We describe online collaborative communities by tripartite networks, the nodes being persons, items and tags. We introduce projection methods in order to uncover the structures of the networks, i.e. communities of users, genre families... <br />To do so, we focus on the correlations between the nodes, depending on their profiles, and use percolation techniques that consist in removing less correlated links and observing the shaping of disconnected islands. The structuring of the network is visualised by using a tree representation. The notion of diversity in the system is also discussed.} }

%0 = misc %A = Lambiotte, R. and Ausloos, M. %B = } %C = %D = 2005 %I = %T = Collaborative tagging as a tripartite network} %U = http://arxiv.org/abs/cs.DS/0512090

@book{Breiman84, author = {Breiman, L. and Friedman, J. H. and Olshen, R. A. and Stone, C. J.}, title = {Classification and regression trees}, publisher = {Wadsworth Publishing Company}, year = {1984}, keywords = {FCA, OntologyHandbook} }

%0 = book %A = Breiman, L. and Friedman, J. H. and Olshen, R. A. and Stone, C. J. %D = 1984 %I = Wadsworth Publishing Company %T = Classification and regression trees

@inproceedings{Gardarin98, author = {Gardarin, G. and Pucheral, P. and Wu, F.}, title = {Bitmap based algorithms for mining association rules}, booktitle = {Actes des 14�mes journ�es Bases de Donn�es Avanc�es (BDA'98)}, year = {1998}, pages = {157--175}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Gardarin, G. and Pucheral, P. and Wu, F. %B = Actes des 14�mes journ�es Bases de Donn�es Avanc�es (BDA'98) %D = 1998 %T = Bitmap based algorithms for mining association rules

@inproceedings{hjss06bibsonomy, author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd}, title = {BibSonomy: A Social Bookmark and Publication Sharing System}, booktitle = {Proc. of the ICCS 2006 Conceptual Structures Tool Interoperability
Workshop}, year = {2006}, note = {(to appear)}, keywords = {FCA, OntologyHandbook, bibsonomy, bookmarking, folksonomy, iccs, social} }

%0 = inproceedings %A = Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd %B = Proc. of the ICCS 2006 Conceptual Structures Tool Interoperability
Workshop %D = 2006 %T = BibSonomy: A Social Bookmark and Publication Sharing System

Social bookmark tools are rapidly emerging on the Web. In such
stems users are setting up lightweight conceptual structures
lled folksonomies. The reason for their immediate success is the
ct that no specific skills are needed for participating. In this
per we specify a formal model for folksonomies and briefly describe
r own system BibSonomy, which allows for sharing both bookmarks
d publication references in a kind of personal library.

@inproceedings{hotho2006bibsonomy, author = {Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd}, title = {BibSonomy: A Social Bookmark and Publication Sharing System}, editor = {de Moor, Aldo and Polovina, Simon and Delugach, Harry}, booktitle = {Proceedings of the First Conceptual Structures Tool Interoperability Workshop at the 14th International Conference on Conceptual Structures}, publisher = {Aalborg Universitetsforlag}, address = {Aalborg}, year = {2006}, pages = {87-102}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006bibsonomy.pdf}, isbn = {87-7307-769-0}, keywords = {2006, FCA, OntologyHandbook, bibsonomy, bookmarking, folksonomy, iccs, l3s, myown, nepomuk, social, tagorapub}, abstract = {Social bookmark tools are rapidly emerging on the Web. In such
stems users are setting up lightweight conceptual structures
lled folksonomies. The reason for their immediate success is the
ct that no specific skills are needed for participating. In this
per we specify a formal model for folksonomies and briefly describe
r own system BibSonomy, which allows for sharing both bookmarks
d publication references in a kind of personal library.} }

%0 = inproceedings %A = Hotho, Andreas and Jäschke, Robert and Schmitz, Christoph and Stumme, Gerd %B = Proceedings of the First Conceptual Structures Tool Interoperability Workshop at the 14th International Conference on Conceptual Structures %C = Aalborg %D = 2006 %I = Aalborg Universitetsforlag %T = BibSonomy: A Social Bookmark and Publication Sharing System %U = http://www.kde.cs.uni-kassel.de/stumme/papers/2006/hotho2006bibsonomy.pdf

@inproceedings{Brin97b, author = {Brin, S. and Motwani, R. and Silverstein, C.}, title = {Beyond market baskets: Generalizing association rules to correlation}, booktitle = {Proceedings of the 1997 ACM SIGMOD international conference on Management
of Data (SIGMOD'97)}, publisher = {ACM Press}, year = {1997}, pages = {265--276}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Brin, S. and Motwani, R. and Silverstein, C. %B = Proceedings of the 1997 ACM SIGMOD international conference on Management
of Data (SIGMOD'97) %D = 1997 %I = ACM Press %T = Beyond market baskets: Generalizing association rules to correlation

@incollection{Heckerman96, author = {Heckerman, D.}, title = {Bayesian networks for knowledge discovery}, editor = {Fayyad, U.M. and Piatetsky-Shapiro, G. and Smyth, P. and Uthurusamy, R.}, booktitle = {Advances in Knowledge Discovery and Data Mining}, publisher = {AAAI Press}, year = {1996}, pages = {273--305}, keywords = {FCA, OntologyHandbook} }

%0 = incollection %A = Heckerman, D. %B = Advances in Knowledge Discovery and Data Mining %D = 1996 %I = AAAI Press %T = Bayesian networks for knowledge discovery

We propose an approach for supporting attribute exploration by web information retrieval, in particular by posing appropriate queries to search engines, crowd sourcing systems, and the linked open data cloud. We discuss underlying general assumptions for this to work and the degree to which these can be taken for granted.

@inproceedings{jaschke2013attribute, author = {Jäschke, Robert and Rudolph, Sebastian}, title = {Attribute Exploration on the Web}, editor = {Cellier, Peggy and Distel, Felix and Ganter, Bernhard}, booktitle = {Contributions to the 11th International Conference on Formal Concept Analysis}, year = {2013}, pages = {19--34}, url = {http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-113133}, keywords = {2013, acquisition, analysis, attribute, computing, concept, crowdsourcing, data, exploration, fca, formal, human, information, ir, iteg, knowledge, l3s, linked, lod, open, retrieval, search, sparql, web}, abstract = {We propose an approach for supporting attribute exploration by web information retrieval, in particular by posing appropriate queries to search engines, crowd sourcing systems, and the linked open data cloud. We discuss underlying general assumptions for this to work and the degree to which these can be taken for granted.} }

%0 = inproceedings %A = Jäschke, Robert and Rudolph, Sebastian %B = Contributions to the 11th International Conference on Formal Concept Analysis %D = 2013 %T = Attribute Exploration on the Web %U = http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-113133

@inproceedings{boulicaut00approximation, author = {Boulicaut, Jean-Francois and Bykowski, Artur and Rigotti, Christophe}, title = {Approximation of Frequency Queries by Means of Free-Sets}, booktitle = {PKDD '00: Proceedings of the 4th European Conference on Principles
of Data Mining and Knowledge Discovery}, publisher = {Springer-Verlag}, address = {London, UK}, year = {2000}, pages = {75--85}, isbn = {3-540-41066-X}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Boulicaut, Jean-Francois and Bykowski, Artur and Rigotti, Christophe %B = PKDD '00: Proceedings of the 4th European Conference on Principles
of Data Mining and Knowledge Discovery %C = London, UK %D = 2000 %I = Springer-Verlag %T = Approximation of Frequency Queries by Means of Free-Sets

@article{Godin94, author = {Godin, R. and Missaoui, R.}, title = {An incremental concept formation approach for learning from databases}, journal = {Theoretical Computer Science : Special issue on formal methods in
databases and software engineering}, publisher = {Elsevier Science}, year = {1994}, volume = {133}, number = {2}, pages = {387--419}, keywords = {FCA, OntologyHandbook} }

%0 = article %A = Godin, R. and Missaoui, R. %D = 1994 %I = Elsevier Science %T = An incremental concept formation approach for learning from databases

@inproceedings{Gupta95, author = {Gupta, A. and Harinarayan, V. and Quass, D.}, title = {Aggregate-query processing in data warehousing environments}, booktitle = {Proceedings of the 21st international conference on Very Large Data
Bases (VLDB'95)}, publisher = {Morgan Kaufmann}, year = {1995}, pages = {358--369}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Gupta, A. and Harinarayan, V. and Quass, D. %B = Proceedings of the 21st international conference on Very Large Data
Bases (VLDB'95) %D = 1995 %I = Morgan Kaufmann %T = Aggregate-query processing in data warehousing environments

@proceedings{duquenne02advanced,, title = {Advances in Formal Concept Analysis for Knowledge Discovery in Databases. Proc. Workshop FCAKDD of the 15th European
Conference on Artificial Intelligence (ECAI 2002)}, editor = {Duquenne, V. and Ganter, B. and Liquiere, M. and Nguifo, E. M. and Stumme, G.}, address = {Lyon, France}, year = {2002}, url = {http://www.lirmm.fr/~liquiere/Documents/FCAKDDProceedings2002.pdf}, keywords = {2002, analysis, concept, ecai, fca, formal, myown, proceedings, workshop} }

%0 = proceedings %B = } %C = Lyon, France %D = 2002 %I = %T = Advances in Formal Concept Analysis for Knowledge Discovery in Databases. Proc. Workshop FCAKDD of the 15th European
Conference on Artificial Intelligence (ECAI 2002)} %U = http://www.lirmm.fr/~liquiere/Documents/FCAKDDProceedings2002.pdf

We propose a generalization of Formal Concept Analysis (FCA) in which
sets of attributes are replaced by expressions of an almost arbitrary
logic. We prove that all FCA can be reconstructed on this basis.
We show that from any logic that is used in place of sets of attributes
can be derived a contextualized logic that takes into account the
formal context and that is isomorphic to the concept lattice. We
then justify the generalization of FCA compared with existing extensions
and in the perspective of its application to information systems.

@inproceedings{ferre00logical, author = {Ferr�, S. and Ridoux, O.}, title = {A Logical Generalization of Formal Concept Analysis}, editor = {Mineau, G. and Ganter, B.}, booktitle = {Int. Conf. Conceptual Structures}, series = {LNCS 1867}, publisher = {Springer}, year = {2000}, pages = {371--384}, keywords = {FCA, OntologyHandbook, concept_analysis, context, information_system, logic}, abstract = {We propose a generalization of Formal Concept Analysis (FCA) in which
sets of attributes are replaced by expressions of an almost arbitrary
logic. We prove that all FCA can be reconstructed on this basis.
We show that from any logic that is used in place of sets of attributes
can be derived a contextualized logic that takes into account the
formal context and that is isomorphic to the concept lattice. We
then justify the generalization of FCA compared with existing extensions
and in the perspective of its application to information systems.} }

%0 = inproceedings %A = Ferr�, S. and Ridoux, O. %B = Int. Conf. Conceptual Structures %D = 2000 %I = Springer %T = A Logical Generalization of Formal Concept Analysis

The theory of concept (or Galois) lattices provides a simple and formal approach to conceptual clustering. In this paper we present GALOIS, a system that automates and applies this theory. The algorithm utilized by GALOIS to build a concept lattice is incremental and efficient, each update being done in time at most quadratic in the number of objects in the lattice. Also, the algorithm may incorporate background information into the lattice, and through clustering, extend the scope of the theory. The application we present is concerned with information retrieval via browsing, for which we argue that concept lattices may represent major support structures. We describe a prototype user interface for browsing through the concept lattice of a document-term relation, possibly enriched with a thesaurus of terms. An experimental evaluation of the system performed on a medium-sized bibliographic database shows good retrieval performance and a significant improvement after the introduction of background knowledge.
-

@article{keyhere, author = {Carpineto, Claudio and Romano, Giovanni}, title = {A lattice conceptual clustering system and its application to browsing retrieval}, journal = {Machine Learning}, year = {1996}, volume = {24}, number = {2}, pages = {95--122}, url = {http://dx.doi.org/10.1007/BF00058654}, keywords = {analysis, carpineto, clustering, concept, fca, formal, information, ir, retrieval}, abstract = {The theory of concept (or Galois) lattices provides a simple and formal approach to conceptual clustering. In this paper we present GALOIS, a system that automates and applies this theory. The algorithm utilized by GALOIS to build a concept lattice is incremental and efficient, each update being done in time at most quadratic in the number of objects in the lattice. Also, the algorithm may incorporate background information into the lattice, and through clustering, extend the scope of the theory. The application we present is concerned with information retrieval via browsing, for which we argue that concept lattices may represent major support structures. We describe a prototype user interface for browsing through the concept lattice of a document-term relation, possibly enriched with a thesaurus of terms. An experimental evaluation of the system performed on a medium-sized bibliographic database shows good retrieval performance and a significant improvement after the introduction of background knowledge. ER -} }

%0 = article %A = Carpineto, Claudio and Romano, Giovanni %D = 1996 %T = A lattice conceptual clustering system and its application to browsing retrieval %U = http://dx.doi.org/10.1007/BF00058654

@inproceedings{stumme05finite, author = {Stumme, Gerd}, title = {A Finite State Model for On-Line Analytical Processing in
Triadic Contexts}, editor = {Ganter, Bernhard and Godin, Robert}, booktitle = {Proc. 3rd Intl. Conf. on Formal Concept Analysis}, series = {Lecture Notes in Computer Science}, publisher = {Springer}, address = {Heidelberg}, year = {2005}, volume = {3403}, pages = {315-328}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2005/stumme2005finite.pdf}, isbn = {3-540-24525-1}, keywords = {2005, fca, folksonomies, itegpub, l3s, myown, olap, triadic} }

%0 = inproceedings %A = Stumme, Gerd %B = Proc. 3rd Intl. Conf. on Formal Concept Analysis %C = Heidelberg %D = 2005 %I = Springer %T = A Finite State Model for On-Line Analytical Processing in
Triadic Contexts %U = http://www.kde.cs.uni-kassel.de/stumme/papers/2005/stumme2005finite.pdf

@inproceedings{Klemettinen97, author = {Klemettinen, M. and Mannila, H. and Toivonen, H.}, title = {A data-mining methodology and its application to semi-automatic knowledge
acquisition}, booktitle = {Proceedings of the 8th international conference on Database and Expert
systems Applications (DEXA'97)}, series = {Lecture Notes in Computer Science, Vol. 1308}, publisher = {Springer-Verlag}, year = {1997}, pages = {670--677}, keywords = {FCA, OntologyHandbook} }

%0 = inproceedings %A = Klemettinen, M. and Mannila, H. and Toivonen, H. %B = Proceedings of the 8th international conference on Database and Expert
systems Applications (DEXA'97) %D = 1997 %I = Springer-Verlag %T = A data-mining methodology and its application to semi-automatic knowledge
acquisition

@inproceedings{Bykowski01condensed, author = {Bykowski, Artur and Rigotti, Christophe}, title = {A condensed representation to find frequent patterns.}, booktitle = {PODS}, year = {2001}, url = {http://dblp.uni-trier.de/db/conf/pods/pods2001.html#BykowskiR01}, keywords = {FCA, OntologyHandbook, dblp} }

%0 = inproceedings %A = Bykowski, Artur and Rigotti, Christophe %B = PODS %D = 2001 %T = A condensed representation to find frequent patterns. %U = http://dblp.uni-trier.de/db/conf/pods/pods2001.html#BykowskiR01