@incollection{wray2011exploring,
  abstract = {Within the cultural informatics community, there is a strong desire to mine and understand relationships within and among collections of objects. In this paper we describe a case study of applied },
  author = {Wray, Tim and Eklund, Peter},
  booktitle = {Formal Concept Analysis},
  doi = {10.1007/978-3-642-20514-9_19},
  editor = {Valtchev, Petko and Jäschke, Robert},
  interhash = {63a1dd1d7e53a545b10ced96469aa2cf},
  intrahash = {8b0b6e80e3f9344120e24111e86efcb0},
  isbn = {978-3-642-20513-2},
  language = {English},
  pages = {251-266},
  publisher = {Springer Berlin Heidelberg},
  series = {Lecture Notes in Computer Science},
  title = {Exploring the Information Space of Cultural Collections Using Formal Concept Analysis},
  url = {http://dx.doi.org/10.1007/978-3-642-20514-9_19},
  volume = 6628,
  year = 2011
}

@incollection{gonzalezcalabozo2011expression,
  abstract = {DNA micro-arrays are a mechanism for eliciting gene expression values, the concentration of the transcription products of a set of genes, under different chemical conditions. The phenomena of interest—up-regulation, down-regulation and co-regulation—are hypothesized to stem from the functional relationships among transcription products.},
  author = {González Calabozo, JoséMaría and Peláez-Moreno, Carmen and Valverde-Albacete, FranciscoJosé},
  booktitle = {Formal Concept Analysis},
  doi = {10.1007/978-3-642-20514-9_11},
  editor = {Valtchev, Petko and Jäschke, Robert},
  interhash = {e7ab7a1eb367c8d8b9a12c5d65727217},
  intrahash = {9cbde0288d6e5ff5e6cf92796acef0a1},
  isbn = {978-3-642-20513-2},
  language = {English},
  pages = {119-134},
  publisher = {Springer Berlin Heidelberg},
  series = {Lecture Notes in Computer Science},
  title = {Gene Expression Array Exploration Using \mathcal{K}-Formal Concept Analysis},
  url = {http://dx.doi.org/10.1007/978-3-642-20514-9_11},
  volume = 6628,
  year = 2011
}

@incollection{lakhal2005efficient,
  abstract = {Association rules are a popular knowledge discovery technique for warehouse basket analysis. They indicate which items of the warehouse are frequently bought together. The problem of association rule mining has first been stated in 1993. Five years later, several research groups discovered that this problem has a strong connection to },
  author = {Lakhal, Lotfi and Stumme, Gerd},
  booktitle = {Formal Concept Analysis},
  doi = {10.1007/11528784_10},
  editor = {Ganter, Bernhard and Stumme, Gerd and Wille, Rudolf},
  interhash = {f5777a0f9dccfcf4f9968119d77297fc},
  intrahash = {fbb41ddbb0a52d1ecca438655e652f09},
  isbn = {978-3-540-27891-7},
  language = {English},
  pages = {180-195},
  publisher = {Springer Berlin Heidelberg},
  series = {Lecture Notes in Computer Science},
  title = {Efficient Mining of Association Rules Based on Formal Concept Analysis},
  url = {http://dx.doi.org/10.1007/11528784_10},
  volume = 3626,
  year = 2005
}

@incollection{ferre2007efficient,
  abstract = {Strings are an important part of most real application multi-valued contexts. Their conceptual treatment requires the definition of },
  author = {Ferré, Sébastien},
  booktitle = {Formal Concept Analysis},
  doi = {10.1007/978-3-540-70901-5_7},
  editor = {Kuznetsov, SergeiO. and Schmidt, Stefan},
  interhash = {133009b4ec80fb0de399a0ce54142599},
  intrahash = {ba4fe6826e3895f2aab04d0f8b59c880},
  isbn = {978-3-540-70828-5},
  language = {English},
  pages = {98-113},
  publisher = {Springer Berlin Heidelberg},
  series = {Lecture Notes in Computer Science},
  title = {The Efficient Computation of Complete and Concise Substring Scales with Suffix Trees},
  url = {http://dx.doi.org/10.1007/978-3-540-70901-5_7},
  volume = 4390,
  year = 2007
}

@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{trant2009studying,
  abstract = {This paper reviews research into social tagging and folksonomy (as reflected in about 180 sources published through December 2007). Methods of researching the contribution of social tagging and folksonomy are described, and outstanding research questions are presented. This is a new area of research, where theoretical perspectives and relevant research methods are only now being defined. This paper provides a framework for the study of folksonomy, tagging and social tagging systems. Three broad approaches are identified, focusing first, on the folksonomy itself (and the role of tags in indexing and retrieval); secondly, on tagging (and the behaviour of users); and thirdly, on the nature of social tagging systems (as socio-technical frameworks).},
  author = {Trant, Jennifer},
  editor = {IMLS},
  interhash = {5490334e34a62eff630294c63ee864f0},
  intrahash = {39b779d7be72022c835f34a98dc25453},
  issn = {1368-7506},
  journal = {Journal of Digital Information},
  number = 1,
  title = {Studying Social Tagging and Folksonomy: A Review and Framework},
  type = {Text.Serial.Journal},
  url = {https://journals.tdl.org/jodi/index.php/jodi/article/view/269},
  volume = 10,
  year = 2009
}

@incollection{tagging-cattuto,
  abstract = {{Collaborative tagging systems have nowadays become important data sources for populating semantic web applications. For tasks like synonym detection and discovery of concept hierarchies, many researchers introduced measures of tag similarity. Even though most of these measures appear very natural, their design often seems to be rather ad hoc, and the underlying assumptions on the notion of similarity are not made explicit. A more systematic characterization and validation of tag similarity in terms of formal representations of knowledge is still lacking. Here we address this issue and analyze several measures of tag similarity: Each measure is computed on data from the social bookmarking system del.icio.us and a semantic grounding is provided by mapping pairs of similar tags in the folksonomy to pairs of synsets in Wordnet, where we use validated measures of semantic distance to characterize the semantic relation between the mapped tags. This exposes important features of the investigated similarity measures and indicates which ones are better suited in the context of a given semantic application.}},
  author = {Cattuto, Ciro and Benz, Dominik and Hotho, Andreas and Stumme, Gerd},
  booktitle = {The Semantic Web - ISWC 2008},
  citeulike-article-id = {4718854},
  citeulike-linkout-0 = {http://dx.doi.org/10.1007/978-3-540-88564-1\_39},
  citeulike-linkout-1 = {http://www.springerlink.com/content/9044260283881v78},
  doi = {10.1007/978-3-540-88564-1\_39},
  editor = {Sheth, Amit and Staab, Steffen and Dean, Mike and Paolucci, Massimo and Maynard, Diana and Finin, Timothy and Thirunarayan, Krishnaprasad},
  interhash = {b44538648cfd476d6c94e30bc6626c86},
  intrahash = {022ccb7184fcd0e43092fca13fd56a00},
  journal = {The Semantic Web - ISWC 2008},
  pages = {615--631},
  posted-at = {2011-09-09 20:06:23},
  priority = {2},
  publisher = {Springer Berlin / Heidelberg},
  series = {Lecture Notes in Computer Science},
  title = {{Semantic Grounding of Tag Relatedness in Social Bookmarking Systems}},
  url = {http://tagora-project.eu/wp-content/2009/09/cattuto_iswc2008.pdf},
  volume = 5318,
  year = 2008
}

@article{white1981author,
  abstract = {It is shown that the mapping of a particular area of science, in this case information science, can be done using authors as units of analysis and the cocitations of pairs of authors as the variable that indicates their “distances” from each other. The analysis assumes that the more two authors are cited together, the closer the relationship between them. The raw data are cocitation counts drawn online from Social Scisearch (Social Sciences Citation Index) over the period 1972–1979. The resulting map shows (1) identifiable author groups (akin to “schools”) of information science, (2) locations of these groups with respect to each other, (3) the degree of centrality and peripherality of authors within groups, (4) proximities of authors within group and across group boundaries (“border authors” who seem to connect various areas of research), and (5) positions of authors with respect to the map's axes, which were arbitrarily set spanning the most divergent groups in order to aid interpretation. Cocitation analysis of authors offers a new technique that might contribute to the understanding of intellectual structure in the sciences and possibly in other areas to the extent that those areas rely on serial publications. The technique establishes authors, as well as documents, as an effective unit in analyzing subject specialties.},
  author = {White, Howard D. and Griffith, Belver C.},
  doi = {10.1002/asi.4630320302},
  interhash = {9d5d0acf1873abf4f57eddd875b8ad90},
  intrahash = {c44a512137b3e8f3f8c9c91e9c7b4a95},
  issn = {1097-4571},
  journal = {Journal of the American Society for Information Science},
  number = 3,
  pages = {163--171},
  publisher = {Wiley},
  title = {Author cocitation: A literature measure of intellectual structure},
  url = {http://dx.doi.org/10.1002/asi.4630320302},
  volume = 32,
  year = 1981
}

@article{small1973cocitation,
  abstract = {A new form of document coupling called co-citation is defined as the frequency with which two documents are cited together. The co-citation frequency of two scientific papers can be determined by comparing lists of citing documents in the Science Citation Index and counting identical entries. Networks of co-cited papers can be generated for specific scientific specialties, and an example is drawn from the literature of particle physics. Co-citation patterns are found to differ significantly from bibliographic coupling patterns, but to agree generally with patterns of direct citation. Clusters of co-cited papers provide a new way to study the specialty structure of science. They may provide a new approach to indexing and to the creation of SDI profiles.},
  author = {Small, Henry},
  doi = {10.1002/asi.4630240406},
  interhash = {dfbb7636c96853cc258878548c12d12f},
  intrahash = {1dc18dfe50667ff19d5cfa9d52d3e37b},
  issn = {1097-4571},
  journal = {Journal of the American Society for Information Science},
  number = 4,
  pages = {265--269},
  publisher = {Wiley Subscription Services, Inc., A Wiley Company},
  title = {Co-citation in the scientific literature: A new measure of the relationship between two documents},
  url = {http://dx.doi.org/10.1002/asi.4630240406},
  volume = 24,
  year = 1973
}