@article{poelmans2013formal2,
  abstract = {Abstract This is the second part of a large survey paper in which we analyze recent literature on Formal Concept Analysis (FCA) and some closely related disciplines using FCA. We collected 1072 papers published between 2003 and 2011 mentioning terms related to Formal Concept Analysis in the title, abstract and keywords. We developed a knowledge browsing environment to support our literature analysis process. We use the visualization capabilities of \{FCA\} to explore the literature, to discover and conceptually represent the main research topics in the \{FCA\} community. In this second part, we zoom in on and give an extensive overview of the papers published between 2003 and 2011 which applied FCA-based methods for knowledge discovery and ontology engineering in various application domains. These domains include software mining, web analytics, medicine, biology and chemistry data. },
  author = {Poelmans, Jonas and Ignatov, Dmitry I. and Kuznetsov, Sergei O. and Dedene, Guido},
  doi = {http://dx.doi.org/10.1016/j.eswa.2013.05.009},
  interhash = {2a69c00103c8bde11fccfb70efcd16d0},
  intrahash = {fdfbf5941c34042ddcb5fbbb58bfe9c1},
  issn = {0957-4174},
  journal = {Expert Systems with Applications },
  number = 16,
  pages = {6538 - 6560},
  title = {Formal concept analysis in knowledge processing: A survey on applications },
  url = {http://www.sciencedirect.com/science/article/pii/S0957417413002959},
  volume = 40,
  year = 2013
}

@article{poelmans2013formal1,
  abstract = {Abstract This is the first part of a large survey paper in which we analyze recent literature on Formal Concept Analysis (FCA) and some closely related disciplines using FCA. We collected 1072 papers published between 2003 and 2011 mentioning terms related to Formal Concept Analysis in the title, abstract and keywords. We developed a knowledge browsing environment to support our literature analysis process. We use the visualization capabilities of \{FCA\} to explore the literature, to discover and conceptually represent the main research topics in the \{FCA\} community. In this first part, we zoom in on and give an extensive overview of the papers published between 2003 and 2011 on developing FCA-based methods for knowledge processing. We also give an overview of the literature on \{FCA\} extensions such as pattern structures, logical concept analysis, relational concept analysis, power context families, fuzzy FCA, rough FCA, temporal and triadic concept analysis and discuss scalability issues. },
  author = {Poelmans, Jonas and Kuznetsov, Sergei O. and Ignatov, Dmitry I. and Dedene, Guido},
  doi = {http://dx.doi.org/10.1016/j.eswa.2013.05.007},
  interhash = {7c70b9621e962c7688ee8ea2670af869},
  intrahash = {ba0e43c2318a5433d9a3d9a253dea6ca},
  issn = {0957-4174},
  journal = {Expert Systems with Applications },
  number = 16,
  pages = {6601 - 6623},
  title = {Formal Concept Analysis in knowledge processing: A survey on models and techniques },
  url = {http://www.sciencedirect.com/science/article/pii/S0957417413002935},
  volume = 40,
  year = 2013
}

@article{poelmans2012semiautomated,
  abstract = {We propose an iterative and human-centred knowledge discovery methodology based on formal concept analysis. The proposed approach recognizes the important role of the domain expert in mining real-world enterprise applications and makes use of specific domain knowledge, including human intelligence and domain-specific constraints. Our approach was empirically validated at the Amsterdam-Amstelland police to identify suspects and victims of human trafficking in 266,157 suspicious activity reports. Based on guidelines of the Attorney Generals of the Netherlands, we first defined multiple early warning indicators that were used to index the police reports. Using concept lattices, we revealed numerous unknown human trafficking and loverboy suspects. In-depth investigation by the police resulted in a confirmation of their involvement in illegal activities resulting in actual arrestments been made. Our human-centred approach was embedded into operational policing practice and is now successfully used on a daily basis to cope with the vastly growing amount of unstructured information.},
  author = {Poelmans, Jonas and Elzinga, Paul and Ignatov, Dmitry I. and Kuznetsov, Sergei O.},
  doi = {10.1080/03081079.2012.721662},
  eprint = {http://www.tandfonline.com/doi/pdf/10.1080/03081079.2012.721662},
  interhash = {18d6f6312af57cc72d7e26de4903dc9f},
  intrahash = {9bb41c50dd5333f94a807482489c0732},
  journal = {International Journal of General Systems},
  number = 8,
  pages = {774--804},
  title = {Semi-automated knowledge discovery: identifying and profiling human trafficking},
  url = {http://www.tandfonline.com/doi/abs/10.1080/03081079.2012.721662},
  volume = 41,
  year = 2012
}

@inproceedings{poelmans2011mining,
  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. },
  author = {Poelmans, Jonas and Elzinga, Paul and Viaene, Stijn and Dedene, Guido and Kuznetsov, Sergei O.},
  booktitle = {Industrial Conference on Data Mining - Poster and Industry Proceedings},
  editor = {Perner, Petra},
  interhash = {b44d11ea5b5a4df8ee30a9c572d82051},
  intrahash = {164c37be60c1a47d1727ad9b82f01237},
  isbn = {978-3-942954-06-4},
  pages = {82--96},
  publisher = {IBaI Publishing},
  title = {Text Mining Scientific Papers: a Survey on {FCA}-based Information Retrieval Research.},
  url = {http://dblp.uni-trier.de/db/conf/incdm/incdm2011p.html#PoelmansEVDK11},
  year = 2011
}

@article{kuznetsov2002comparing,
  author = {Kuznetsov, Sergei O. and Obiedkov, Sergei A.},
  doi = {10.1080/09528130210164170},
  eprint = {http://www.tandfonline.com/doi/pdf/10.1080/09528130210164170},
  interhash = {8d58be3c9b7cec4767458436c70dc532},
  intrahash = {582910e7a14a80469b2cb328fa0d9884},
  journal = {Journal of Experimental & Theoretical Artificial Intelligence},
  number = {2-3},
  pages = {189-216},
  title = {Comparing performance of algorithms for generating concept lattices},
  url = {http://www.tandfonline.com/doi/abs/10.1080/09528130210164170},
  volume = 14,
  year = 2002
}

@article{1393768,
  abstract = {Implications of a formal context obey Armstrong rules, which allows one to define a minimal (in the number of implications) implication basis, called Duquenne-Guigues basis or stem base in the literature. In this paper we show how implications are reduced to functional dependencies and prove that the problem of determining the size of the stem base is a #P-complete problem.},
  address = {Amsterdam, The Netherlands, The Netherlands},
  author = {Kuznetsov, Sergei O. and Obiedkov, Sergei},
  doi = {http://dx.doi.org/10.1016/j.dam.2007.04.014},
  interhash = {984c199174cd75cfb8e315494a1a1477},
  intrahash = {5cc734b8c96126d43e9b6c1fc91933d9},
  issn = {0166-218X},
  journal = {Discrete Appl. Math.},
  number = 11,
  pages = {1994--2003},
  publisher = {Elsevier Science Publishers B. V.},
  title = {Some decision and counting problems of the Duquenne-Guigues basis of implications},
  url = {http://portal.acm.org/citation.cfm?id=1393768},
  volume = 156,
  year = 2008
}

@inproceedings{ganter00formalizing,
  author = {Ganter, Bernhard and Kuznetsov, Sergei O.},
  booktitle = {ICCS},
  crossref = {conf/iccs/2000},
  date = {2002-01-03},
  editor = {Ganter, Bernhard and Mineau, Guy W.},
  interhash = {280d81720a09782c64524d5a19cfd912},
  intrahash = {96a1d20f983e8bff397e9370e0400fa2},
  isbn = {3-540-67859-X},
  pages = {342-356},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  title = {Formalizing Hypotheses with Concepts},
  url = {http://dblp.uni-trier.de/db/conf/iccs/iccs2000.html#GanterK00},
  volume = 1867,
  year = 2000
}