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    AuthorTitleYearJournal/ProceedingsReftypeDOI/URL
    Jäschke, R. & Rudolph, S. Attribute Exploration on the Web 2013 Contributions to the 11th International Conference on Formal Concept Analysis, pp. 19-34  inproceedings URL 
    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.
    BibTeX:
    @inproceedings{jaschke2013attribute,
      author = {Jäschke, Robert and Rudolph, Sebastian},
      title = {Attribute Exploration on the Web},
      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}
    }
    
    Doerfel, S., Jäschke, R. & Stumme, G. Publication Analysis of the Formal Concept Analysis Community 2012
    Vol. 7278ICFCA 2012, pp. 77-95 
    inproceedings URL 
    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.
    BibTeX:
    @inproceedings{doerfel2012publication,
      author = {Doerfel, Stephan and Jäschke, Robert and Stumme, Gerd},
      title = {Publication Analysis of the Formal Concept Analysis Community},
      booktitle = {ICFCA 2012},
      publisher = {Springer},
      year = {2012},
      volume = {7278},
      pages = {77--95},
      url = {https://www.kde.cs.uni-kassel.de/pub/pdf/doerfel2012publication.pdf}
    }
    
    Poelmans, J., Ignatov, D., Viaene, S., Dedene, G. & Kuznetsov, S. Text Mining Scientific Papers: A Survey on FCA-Based Information Retrieval Research 2012
    Vol. 7377Advances in Data Mining. Applications and Theoretical Aspects, pp. 273-287 
    incollection DOI URL 
    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.
    BibTeX:
    @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},
      booktitle = {Advances in Data Mining. Applications and Theoretical Aspects},
      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 = {http://dx.doi.org/10.1007/978-3-642-31488-9_22}
    }
    
    Hotho, A., Jäschke, R., Schmitz, C. & Stumme, G. Information Retrieval in Folksonomies: Search and Ranking 2006 Proceedings of the 3rd European Semantic Web Conference, pp. 411-426  inproceedings  
    BibTeX:
    @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},
      publisher = {Springer},
      year = {2006},
      pages = {411-426}
    }
    
    Cimiano, P., Hotho, A., Stumme, G. & Tane, J. Conceptual Knowledge Processing with Formal Concept Analysis and Ontologies 2004
    Vol. 2961Concept Lattices, pp. 189-207 
    incollection URL 
    BibTeX:
    @incollection{cimiano2004conceptual,
      author = {Cimiano, Philipp and Hotho, Andreas and Stumme, Gerd and Tane, Julien},
      title = {Conceptual Knowledge Processing with Formal Concept
    Analysis and Ontologies}, booktitle = {Concept Lattices}, publisher = {Springer}, year = {2004}, volume = {2961}, pages = {189--207}, url = {http://dx.doi.org/10.1007/978-3-540-24651-0_18} }
    Calders, T. & Goethals, B. Mining All Non-derivable Frequent Itemsets 2002 PKDD '02: Proceedings of the 6th European Conference on Principles
    of Data Mining and Knowledge Discovery, pp. 74-85 
    inproceedings  
    BibTeX:
    @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}, year = {2002}, pages = {74--85} }
    Stumme, G., Taouil, R., Bastide, Y., Pasquier, N. & Lakhal, L. Computing iceberg concept lattices with TITANIC 2002 Data & Knowledge Engineering
    Vol. 42(2), pp. 189-222 
    article DOI URL 
    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.
    BibTeX:
    @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.},
      year = {2002},
      volume = {42},
      number = {2},
      pages = {189--222},
      url = {http://portal.acm.org/citation.cfm?id=606457},
      doi = {http://dx.doi.org/10.1016/S0169-023X(02)00057-5}
    }
    
    Burdick, D., Calimlim, M. & Gehrke, J. MAFIA: A maximal frequent itemset algorithm for transactional databases 2001 Proc. of the 17th Int. Conf. on Data Engineering  inproceedings  
    BibTeX:
    @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}
    }
    
    Bykowski, A. & Rigotti, C. A condensed representation to find frequent patterns. 2001 PODS  inproceedings URL 
    BibTeX:
    @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}
    }
    
    Bastide, Y. Data Mining: algorithmes par niveau, techniques d'implementation et applications 2000 School: Université de Clermont-Ferrand II  phdthesis  
    BibTeX:
    @phdthesis{Bastide00,
      author = {Bastide, Y.},
      title = {Data Mining: algorithmes par niveau, techniques d'implementation
    
    et applications}, school = {Université de Clermont-Ferrand II}, year = {2000} }
    Boulicaut, J.-F., Bykowski, A. & Rigotti, C. Approximation of Frequency Queries by Means of Free-Sets 2000 PKDD '00: Proceedings of the 4th European Conference on Principles
    of Data Mining and Knowledge Discovery, pp. 75-85 
    inproceedings  
    BibTeX:
    @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}, year = {2000}, pages = {75--85} }
    Burmeister, P. Formal concept analysis with ConImp : Introduction to the basic features 1998   techreport  
    BibTeX:
    @techreport{Burmeister98,
      author = {Burmeister, P.},
      title = {Formal concept analysis with ConImp : Introduction to the
    
    basic features}, year = {1998}, note = {http://www.mathematik.tu-darmstadt.de/~burmeister/ConImpIntro.ps} }
    Fayet, A., Giacometti, A., Laurent, D. & Spyratos, N. Découverte de r�gles pertinentes dans les bases de donn�es 1998 Actes des 14�mes journ�es Bases de Donn�es Avanc�es (BDA'98), pp. 197-211  inproceedings  
    BibTeX:
    @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}
    }
    
    Brin, S., Motwani, R. & Silverstein, C. Beyond market baskets: Generalizing association rules to correlation 1997 Proceedings of the 1997 ACM SIGMOD international conference on Management
    of Data (SIGMOD'97), pp. 265-276 
    inproceedings  
    BibTeX:
    @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} }
    Brin, S., Motwani, R., Ullman, J.D. & Tsur, S. Dynamic itemset counting and implication rules for market basket data 1997 Proceedings of the 1997 ACM SIGMOD international conference on Management
    of Data (SIGMOD'97), pp. 255-264 
    inproceedings  
    BibTeX:
    @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} }
    Fayyad, U.M., Piatetsky-Shapiro, G. & Smyth, P. From data mining to knowledge discovery : An overview 1996 Advances in Knowledge Discovery and Data Mining, pp. 1-30  incollection  
    BibTeX:
    @incollection{Fayyad96c,
      author = {Fayyad, U. M. and Piatetsky-Shapiro, G. and Smyth, P.},
      title = {From data mining to knowledge discovery : An overview},
      booktitle = {Advances in Knowledge Discovery and Data Mining},
      publisher = {AAAI Press},
      year = {1996},
      pages = {1--30}
    }
    
    Fayyad, U.M., Piatetsky-Shapiro, G. & Smyth, P. Knowledge discovery and data mining : Towards a unifying framework 1996 Proceedings of the 2nd international conference on Knowledge Discovery
    and Data mining (KDD'96), pp. 82-88 
    inproceedings  
    BibTeX:
    @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} }
    Feldman, R. & Dagan, I. Knowledge discovery in textual databases 1995 Proceedings of the 1st international conference on Knowledge Discovery
    and Data mining (KDD'95), pp. 112-117 
    inproceedings  
    BibTeX:
    @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} }
    Breiman, L., Friedman, J.H., Olshen, R.A. & Stone, C.J. Classification and regression trees 1984   book  
    BibTeX:
    @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}
    }
    
    Brugger, W. Philosophisches W�rterbuch 1976   book  
    BibTeX:
    @book{brugger76philosophisches,
      author = {Brugger, W.},
      title = {Philosophisches W�rterbuch},
      publisher = {Herder},
      year = {1976}
    }
    

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