@inproceedings{conf/cla/BorchmannH16, author = {Borchmann, Daniel and Hanika, Tom}, booktitle = {CLA}, crossref = {conf/cla/2016}, editor = {Huchard, Marianne and Kuznetsov, Sergei}, ee = {http://ceur-ws.org/Vol-1624/paper5.pdf}, interhash = {e8ddef8aeb9b874f97a1a8230332b7c4}, intrahash = {8af414e45f306527e8316ac681fe7f08}, pages = {57-69}, publisher = {CEUR-WS.org}, series = {CEUR Workshop Proceedings}, title = {Some Experimental Results on Randomly Generating Formal Contexts.}, url = {http://dblp.uni-trier.de/db/conf/cla/cla2016.html#BorchmannH16}, volume = 1624, year = 2016 } @inproceedings{doerfel2012publication, 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. }, address = {Berlin/Heidelberg}, author = {Doerfel, Stephan and Jäschke, Robert and Stumme, Gerd}, booktitle = {ICFCA 2012}, editor = {Domenach, F. and Ignatov, D.I. and Poelmans, J.}, interhash = {f34f31e8dd1e07b1b0a5ab688f10084a}, intrahash = {0ac1296af204a499490bf61a48d03e48}, pages = {77--95}, publisher = {Springer}, series = {Lecture Notes in Artificial Intelligence}, title = {Publication Analysis of the Formal Concept Analysis Community}, url = {https://www.kde.cs.uni-kassel.de/pub/pdf/doerfel2012publication.pdf}, volume = 7278, year = 2012 } @inproceedings{doerfel2012publication, 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. }, address = {Berlin/Heidelberg}, author = {Doerfel, Stephan and Jäschke, Robert and Stumme, Gerd}, booktitle = {ICFCA 2012}, editor = {Domenach, F. and Ignatov, D.I. and Poelmans, J.}, interhash = {f34f31e8dd1e07b1b0a5ab688f10084a}, intrahash = {0ac1296af204a499490bf61a48d03e48}, pages = {77--95}, publisher = {Springer}, series = {Lecture Notes in Artificial Intelligence}, title = {Publication Analysis of the Formal Concept Analysis Community}, url = {https://www.kde.cs.uni-kassel.de/pub/pdf/doerfel2012publication.pdf}, volume = 7278, year = 2012 } @inproceedings{doerfel2012publication, 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. }, address = {Berlin/Heidelberg}, author = {Doerfel, Stephan and Jäschke, Robert and Stumme, Gerd}, booktitle = {Formal Concept Analysis}, doi = {10.1007/978-3-642-29892-9_12}, editor = {Domenach, F. and Ignatov, D.I. and Poelmans, J.}, interhash = {f34f31e8dd1e07b1b0a5ab688f10084a}, intrahash = {9207cd4b1cf7d87c9ae959ac780e152c}, isbn = {978-3-642-29891-2}, month = may, pages = {77--95}, publisher = {Springer}, series = {Lecture Notes in Artificial Intelligence}, title = {Publication Analysis of the Formal Concept Analysis Community}, url = {http://link.springer.com/chapter/10.1007/978-3-642-29892-9_12}, volume = 7278, year = 2012 } @inproceedings{stumme2004iceberg, address = {Heidelberg}, author = {Stumme, Gerd}, booktitle = {Conceptual Structures at Work: 12th International Conference on Conceptual Structures (ICCS 2004)}, comment = {alpha}, editor = {Wolff, Karl Erich and Pfeiffer, Heather D. and Delugach, Harry S.}, interhash = {5e81311b4e69d49a2f0aa7cd3f52b21d}, intrahash = {70b05439d41b24c2476e9eba1f74ec87}, pages = {109-125}, publisher = {Springer}, series = {LNCS}, title = {Iceberg Query Lattices for Datalog}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2004/stumme2004iceberg.pdf}, volume = 3127, year = 2004 } @article{pasquier2005generating, author = {Pasquier, Nicolas and Taouil, Rafik and Bastide, Yves and Stumme, Gerd and Lakhal, Lotfi}, comment = {alpha}, interhash = {cb0ee99fae39f2a5e0af5be9d97978f5}, intrahash = {40f59a7fa7ce5015f9ee81709db89de0}, journal = {Journal Intelligent Information Systems (JIIS)}, number = 1, pages = {29-60}, publisher = {Kluwer Academic Publishers}, title = {Generating a Condensed Representation for Association Rules}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2005/pasquier2005generating.pdf}, volume = 24, year = 2005 } @article{jaeschke08discovering, author = {Jäschke, Robert and Hotho, Andreas and Schmitz, Christoph and Ganter, Bernhard and Stumme, Gerd}, interhash = {cfca594f9dbe30694bfbcdeb40dc4e88}, intrahash = {eb0bdaeab0aa5d4c528c97e2b10770b9}, journal = {Journal of Web Semantics}, number = 1, pages = {38-53}, title = {Discovering Shared Conceptualizations in Folksonomies}, url = {http://dx.doi.org/10.1016/j.websem.2007.11.004}, volume = 6, year = 2008 } @inproceedings{jaeschke06trias, address = {Hong Kong}, author = {Jäschke, Robert and Hotho, Andreas and Schmitz, Christoph and Ganter, Bernhard and Stumme, Gerd}, booktitle = {Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 06)}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICDM.2006.162}, interhash = {b4964c3bdd2991a80873d7080ef6a73e}, intrahash = {e387c294129e11f4221514d5fa807e26}, isbn = {0-7695-2701-9}, issn = {1550-4786}, month = {December}, pages = {907-911}, publisher = {IEEE Computer Society}, title = {TRIAS - An Algorithm for Mining Iceberg Tri-Lattices}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2006/jaeschke2006trias.pdf}, vgwort = {19}, year = 2006 } @inbook{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 Formal Concept Analysis (FCA). In this survey, we will first introduce some basic ideas of this connection along a specific algorithm, \titanic, and show how FCA helps in reducing the number of resulting rules without loss of information, before giving a general overview over the history and state of the art of applying FCA for association rule mining.}, address = {Heidelberg}, author = {Lakhal, Lotfi and Stumme, Gerd}, booktitle = {Formal Concept Analysis: Foundations and Applications}, editor = {Ganter, Bernhard and Stumme, Gerd and Wille, Rudolf}, ee = {http://dx.doi.org/10.1007/11528784_10}, interhash = {f5777a0f9dccfcf4f9968119d77297fc}, intrahash = {2b350f817428e4c6c7259cd279815091}, pages = {180-195}, publisher = {Springer}, series = {LNAI}, title = {Efficient Mining of Association Rules Based on Formal Concept Analysis}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2005/lakhal2005efficient.pdf}, volume = 3626, year = 2005 } @proceedings{valtchev2011formal, abstract = {The present volume features a selection of the papers presented at the 9th International Conference on Formal Concept Analysis (ICFCA 2011). Over the years, the ICFCA conference series has grown into the premier forum for dissemination of research on topics from formal concept analysis (FCA) theory and applications, as well as from the related fields of lattices and partially ordered structures. FCA is a multi-disciplinary field with strong roots in the mathematical theory of partial orders and lattices, with tools originating in computer science and artificial intelligence. FCA emerged in the early 1980s from efforts to restructure lattice theory to promote better communication between lattice theorists and potential users of lattice-based methods for data management. Initially, the central theme was the mathematical formalization of concept and conceptual hierarchy. Since then, the field has developed into a constantly growing research area in its own right with a thriving theoretical community and an increasing number of applications in data and knowledge processing including disciplines such as data visualization, information retrieval, machine learning, software engineering, data analysis, data mining, social networks analysis, etc. ICFCA 2011 was held from May 2 to May 6, 2011, in Nicosia, Cyprus. The program committee received 49 high-quality submissions that were subjected to a highly competitive selection process. Each paper was reviewed by three referees (exceptionally two or four). After a first round, some papers got a definitive acceptance status, while others got accepted conditionally to improvements in their content. The latter got to a second round of reviewing. The overall outcome was the acceptance of 16 papers as regular ones for presentation at the conference and publication in this volume. Another seven papers have still been assessed as valuable for discussion at the conference and were therefore collected in the supplementary proceedings. The regular papers presented hereafter cover advances on a wide range of subjects from FCA and related fields. A first group of papers tackled mathematical problems within the FCA field. A subset thereof focused on factor identification within the incidence relation or its lattice representation (papers by Glodeanu and by Krupka). The remainder of the group proposed characterizations of particular classes of ordered structures (papers by Doerfel and by Meschke et al.). A second group of papers addressed algorithmic problems from FCA and related fields. Two papers approached their problems from an algorithmic complexity viewpoint (papers by Distel and by Babin and Kuznetsov) while the final paper in this group addressed algorithmic problems for general lattices, i.e., not represented as formal contexts, with an FCA-based approach (work by Balcázar and Tîrnăucă). A third group studied alternative approaches for extending the expressive power of the core FCA, e.g., by generalizing the standard one-valued attributes to attributes valued in algebraic rings (work by González Calabozo et al.), by introducing pointer-like attributes, a.k.a. links (paper by Kötters), or by substituting set-shaped concept intents with modal logic expressions (paper by Soldano and Ventos). A fourth group focused on data mining-oriented aspects of FCA: agreement lattices in structured data mining (paper by Nedjar et al.), triadic association rule mining (work by Missaoui and Kwuida) and bi-clustering of numerical data (Kaytoue et al.). An addional paper shed some initial light on a key aspect of FCA-based data analysis and mining, i.e., the filtering of interesting concepts (paper by Belohlavek and Macko). Finally, a set of exciting applications of both basic and enhanced FCA frameworks to practical problems have beed described: in analysis of gene expression data (the already mentioned work by González Calabozo et al.), in web services composition (paper by Azmeh et al.) and in browsing and retrieval of structured data (work by Wray and Eklund). This volume also contains three keynote papers submitted by the invited speakers of the conference. All these contributions constitute a volume of high quality which is the result of the hard work done by the authors, the invited speakers and the reviewers. We therefore wish to thank the members of the Program Committee and of the Editorial Board whose steady involvement and professionalism helped a lot. We would also like to acknowledge the participation of all the external reviewers who sent many valuable comments. Kudos also go to EasyChair for having made the reviewing/editing process a real pleasure. Special thanks go to the Cyprus Tourism Organisation for sponsoring the conference and to the University of Nicosia for hosting it. Finally we wish to thank the Conference Chair Florent Domenach and his colleagues from the Organization Committee for the mountains of energy they put behind the conference organization process right from the beginning in order to make it a total success. We would also like to express our gratitude towards Dr. Peristianis, President of the University of Nicosia, for his personal support. }, address = {Berlin/Heidelberg}, doi = {10.1007/978-3-642-20514-9_2}, editor = {Valtchev, Petko and Jäschke, Robert}, interhash = {a7fd7ebbb14eacc605ff61cf2759cb06}, intrahash = {afd54a24a2eeca1a07f811bd89800d28}, isbn = {978-3-642-20513-2}, month = may, publisher = {Springer}, series = {Lecture Notes in Artificial Intelligence}, title = {Formal Concept Analysis}, url = {http://www.springer.com/computer/ai/book/978-3-642-20513-2}, vgwort = {452}, volume = 6628, year = 2011 } @book{jaeschke2011formal, abstract = {One of the most noticeable innovation that emerged with the advent of the Web 2.0 and the focal point of this thesis are collaborative tagging systems. They allow users to annotate arbitrary resources with freely chosen keywords, so called tags. The tags are used for navigation, finding resources, and serendipitous browsing and thus provide an immediate benefit for the user. By now, several systems for tagging photos, web links, publication references, videos, etc. have attracted millions of users which in turn annotated countless resources. Tagging gained so much popularity that it spread into other applications like web browsers, software packet managers, and even file systems. Therefore, the relevance of the methods presented in this thesis goes beyond the Web 2.0. The conceptual structure underlying collaborative tagging systems is called folksonomy. It can be represented as a tripartite hypergraph with user, tag, and resource nodes. Each edge of the graph expresses the fact that a user annotated a resource with a tag. This social network constitutes a lightweight conceptual structure that is not formalized, but rather implicit and thus needs to be extracted with knowledge discovery methods. In this thesis a new data mining task – the mining of all frequent tri-concepts – is presented, together with an efficient algorithm for discovering such implicit shared conceptualizations. Our approach extends the data mining task of discovering all closed itemsets to three-dimensional data structures to allow for mining folksonomies. Extending the theory of triadic Formal Concept Analysis, we provide a formal definition of the problem, and present an efficient algorithm for its solution. We show the applicability of our approach on three large real-world examples and thereby perform a conceptual clustering of two collaborative tagging systems. Finally, we introduce neighborhoods of triadic concepts as basis for a lightweight visualization of tri-lattices. The social bookmark and publication sharing system BibSonomy, which is currently among the three most popular systems of its kind, has been developed by our research group. Besides being a useful tool for many scientists, it provides interested researchers a basis for the evaluation and integration of their knowledge discovery methods. This thesis introduces BibSonomy as an exemplary collaborative tagging system and gives an overview of its architecture and some of its features. Furthermore, BibSonomy is used as foundation for evaluating and integrating some of the discussed approaches. Collaborative tagging systems usually include tag recommendation mechanisms easing the process of finding good tags for a resource, but also consolidating the tag vocabulary across users. In this thesis we evaluate and compare several recommendation algorithms on large-scale real-world datasets: an adaptation of user-based Collaborative Filtering, a graph-based recommender built on top of the FolkRank algorithm, and simple methods based on counting tag co-occurences. We show that both FolkRank and Collaborative Filtering provide better results than non-personalized baseline methods. Moreover, since methods based on counting tag co-occurrences are computationally cheap, and thus usually preferable for real time scenarios, we discuss simple approaches for improving the performance of such methods. We demonstrate how a simple recommender based on counting tags from users and resources can perform almost as good as the best recommender. Furthermore, we show how to integrate recommendation methods into a real tagging system, record and evaluate their performance by describing the tag recommendation framework we developed for BibSonomy. With the intention to develop, test, and evaluate recommendation algorithms and supporting cooperation with researchers, we designed the framework to be easily extensible, open for a variety of methods, and usable independent from BibSonomy. We also present an evaluation of the framework which demonstrates its power. The folksonomy graph shows specific structural properties that explain its growth and the possibility of serendipitous exploration. Clicklogs of web search engines can be represented as a folksonomy in which queries are descriptions of clicked URLs. The resulting network structure, which we will term logsonomy is very similar to the one of folksonomies. In order to find out about its properties, we analyze the topological characteristics of the tripartite hypergraph of queries, users and bookmarks on a large folksonomy snapshot and on query logs of two large search engines. We find that all of the three datasets exhibit similar structural properties and thus conclude that the clicking behaviour of search engine users based on the displayed search results and the tagging behaviour of collaborative tagging users is driven by similar dynamics. In this thesis we further transfer the folksonomy paradigm to the Social Semantic Desktop – a new model of computer desktop that uses Semantic Web technologies to better link information items. There we apply community support methods to the folksonomy found in the network of social semantic desktops. Thus, we connect knowledge discovery for folksonomies with semantic technologies. Alltogether, the research in this thesis is centered around collaborative tagging systems and their underlying datastructure – folksonomies – and thereby paves the way for the further dissemination of this successful knowledge management paradigm. }, address = {Heidelberg, Germany}, author = {Jäschke, Robert}, interhash = {dcb2cd1cd72ae45d77c4d8755d199405}, intrahash = {9db90c2ff04f514ada9f6b50fde46065}, isbn = {978-3-89838-332-5}, month = jan, publisher = {Akademische Verlagsgesellschaft AKA}, series = {Dissertationen zur Künstlichen Intelligenz}, title = {Formal Concept Analysis and Tag Recommendations in Collaborative Tagging Systems}, url = {http://www.aka-verlag.com/de/detail?ean=978-3-89838-332-5}, vgwort = {413}, volume = 332, year = 2011 } @article{jaeschke2008discovering, abstract = {Social bookmarking tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. Unlike ontologies, shared conceptualizations are not formalized, but rather implicit. We present a new data mining task, the mining of all frequent tri-concepts, together with an efficient algorithm, for discovering these implicit shared conceptualizations. Our approach extends the data mining task of discovering all closed itemsets to three-dimensional data structures to allow for mining folksonomies. We provide a formal definition of the problem, and present an efficient algorithm for its solution. Finally, we show the applicability of our approach on three large real-world examples.}, address = {New York}, author = {Jäschke, Robert and Hotho, Andreas and Schmitz, Christoph and Ganter, Bernhard and Stumme, Gerd}, booktitle = {Semantic Web and Web 2.0}, doi = {10.1016/j.websem.2007.11.004}, editor = {Finin, T. and Mizoguchi, R. and Staab, S.}, interhash = {cfca594f9dbe30694bfbcdeb40dc4e88}, intrahash = {18e8babe208fae2c0342438617b0ec31}, issn = {1570-8268}, journal = {Web Semantics: Science, Services and Agents on the World Wide Web}, month = feb, number = 1, pages = {38--53}, publisher = {Elsevier}, title = {Discovering Shared Conceptualizations in Folksonomies}, url = {http://www.kde.cs.uni-kassel.de/pub/pdf/jaeschke2008discovering.pdf}, vgwort = {59}, volume = 6, year = 2008 } @article{hereth03conceptual, 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.}, author = {Hereth, Joachim and Stumme, Gerd and Wille, Rudolf and Wille, Uta}, comment = {alpha}, interhash = {a9c05101aeb799232425d7651a581684}, intrahash = {edffeb9bd2aaac559f2a6233dd49ae3b}, journal = {Journal of Applied Artificial Intelligence (AAI)}, number = 3, pages = {281-301}, title = {Conceptual Knowledge Discovery - a Human-Centered Approach}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2003/hereth2003conceptual.pdf}, volume = 17, year = 2003 } @proceedings{duquenne02advanced, address = {Lyon, France}, comment = {alpha}, editor = {Duquenne, V. and Ganter, B. and Liquiere, M. and Nguifo, E. M. and Stumme, G.}, interhash = {0d1cc060cbad644c4e5bb7b6bbe93f35}, intrahash = {9fc9512c38ebd6dbd6982fce651da0be}, month = {July 23,}, title = {Advances in Formal Concept Analysis for Knowledge Discovery in Databases. Proc. Workshop FCAKDD of the 15th European Conference on Artificial Intelligence (ECAI 2002)}, url = {http://www.lirmm.fr/~liquiere/Documents/FCAKDDProceedings2002.pdf}, year = 2002 } @techreport{stumme99conceptualknowledge, author = {Stumme, G.}, comment = {alpha}, institution = {TU Darmstadt}, interhash = {c33970150f97bad7972281e38b42738f}, intrahash = {6d562dc043ba698acee8a83ce35bde6e}, title = {Conceptual Knowledge Discovery with Frequent Concept Lattices}, type = {{FB}4-{P}reprint 2043}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/1999/P2043.pdf}, year = 1999 } @inproceedings{prediger99theory, author = {Prediger, S. and Stumme, G.}, booktitle = {Proc. 6th Intl. Workshop Knowledge Representation Meets Databases (KRDB'99)}, comment = {alpha}, editor = {et al, E. Franconi}, interhash = {f8954580726dabd8427ec6e5f5b03a37}, intrahash = {012c6e353faa417521e9c88fc5c89f1e}, note = {Also in: P. Lambrix et al (Eds.): Proc. Intl. Workshop on Description Logics (DL'99). CEUR Workshop Proc. 22, 1999 \url{http://ceur-ws.org/Vol-21}}, title = {Theory-Driven Logical Scaling}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/1999/KRDB99.pdf}, volume = {CEUR Workshop Proc. 21}, year = 1999 } @inproceedings{stumme95geometrical, address = {Heidelberg}, author = {Stumme, Gerd and Wille, Rudolf}, booktitle = {Graph Drawing}, comment = {alpha}, editor = {Tamassia, R. and Tollis, I.G.}, interhash = {0e3ac1bae7ef38507b1ff5b5bc6c4d49}, intrahash = {069db3a0aad592c82f35e1bbf701824f}, pages = {452-459}, publisher = {Springer}, series = {LNCS}, title = {A Geometrical Heuristic for Drawing Concept Lattices}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/1994/P1677-GD94.pdf}, volume = 894, year = 1995 } @mastersthesis{stumme94boolesche, author = {Stumme, Gerd}, comment = {alpha}, interhash = {85d61c34f437517d77f7b49ce1df1349}, intrahash = {545afd2fc553435b9bef5c610a387e69}, school = {TH Darmstadt}, title = {Boolesche {B}egriffe}, type = {Diplomarbeit}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/1994/Diplomarbeit94.pdf}, year = 1994 } @inproceedings{stumme01conceptualclustering, address = {Universität Dortmund 763}, author = {Stumme, G. and Taouil, R. and Bastide, Y. and Lakhal, L.}, booktitle = {Proc. GI-Fachgruppentreffen Maschinelles Lernen (FGML'01)}, editor = {Klinkenberg, R. and Rüping, S. and Fick, A. and Henze, N. and Herzog, C. and Molitor, R. and Schröder, O.}, interhash = {c99f2ae002435208c58f9244d298a10b}, intrahash = {f4ec21d5f63dbc213a3a6eae076c4b62}, month = {October}, title = {Conceptual Clustering with Iceberg Concept Lattices}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2001/FGML01.pdf}, year = 2001 } @inproceedings{bastide00miningminimal, address = {Heidelberg}, author = {Bastide, Y. and Pasquier, N. and Taouil, R. and Stumme, G. and Lakhal, L.}, booktitle = {Computational Logic --- CL 2000 Proc. CL'00}, editor = {Lloyd, J. and Dahl, V. and Furbach, U. and Kerber, M. and Laus, K.-K. and Palamidessi, C. and Pereira, L.M. and Sagiv, Y. and Stuckey, P.J.}, interhash = {dc10d0ad3c40463f049ac775cb250f3d}, intrahash = {25fa3431e7bdd7057f9b80a7385cd718}, page = {972-986}, publisher = {Springer}, series = {LNAI}, title = {Mining Minimal Non-Redundant Association Rules Using Frequent Closed Itemsets}, url = {http://www.kde.cs.uni-kassel.de/stumme/papers/2000/DOOD00.pdf}, volume = 1861, year = 2000 }