BibSonomy publications for /user/stumme/formalFri Nov 27 21:23:21 CET 2009HeidelbergKI 2001: Advances in Artificial Intelligence. KI 2001335-350LNAIIntelligent Structuring and Reducing of Association Rules and with Formal Concept Analysis217420012001 FCA OntologyHandbook analysis association bases closed concept condensed discovery fca formal itemsets kdd knowledge mining myown representations rule rules Tue Jul 14 22:34:36 CEST 2009Amsterdam, The Netherlands, The NetherlandsWeb Semant.138--53Discovering shared conceptualizations in folksonomies62008analysis concept fca formal myown ontologyhandbook trias 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.Fri Jul 03 00:26:53 CEST 2009HeidelbergConceptual Structures: Logical, Linguistic, and Computational Issues. Proc. ICCS '00421-437LNAIConceptual Knowledge Discovery and Data Analysis186720002000 FCA OntologyHandbook analysis ckdd concept conceptual discovery fca formal kdd knowledge myown Fri Jul 03 00:23:48 CEST 2009Heidelberg-BerlinPrinciples of Data Mining and Knowledge Discovery. Proc. PKDD 2000367-374LNAI{CEM} -- A Program for Visualization and Discovery in Email191020002000 analysis cem concept email fca formal mail management manager myown nepomuk Fri Jul 03 00:22:55 CEST 2009SIGKDD Explorations, Special Issue on Scalable Algorithms271-80Mining Frequent Patterns with Counting Inference.220002000 FCA OntologyHandbook analys association closed concept condensed data discovery fca formal frequent itemsets kdd knowledge mining myown representation representations rule rules Fri Jul 03 00:21:06 CEST 2009HeidelbergComputational Logic --- CL 2000 Proc. CL'00LNAIMining Minimal Non-Redundant Association Rules Using Frequent Closed Itemsets186120002000 analys association closed concept condensed data discovery fca formal frequent itemsets kdd knowledge mining myown representation representations rule rules Fri Jul 03 00:19:24 CEST 2009Universität Dortmund 763Proc. GI-Fachgruppentreffen Maschinelles Lernen (FGML'01)OctoberConceptual Clustering with Iceberg Concept Lattices20012001 analysis closed clustering concept conceptual discovery fca formal iceberg itemsets kdd knowledge lattices myown Fri Jul 03 00:14:04 CEST 2009HeidelbergFormal Concept Analysis: Foundations and Applications180-195LNAIEfficient Mining of Association Rules Based on Formal Concept Analysis362620052005 analysis association book closed concept condensed data discovery fca formal itegpub itemsets kdd knowledge l3s mining myown representations rules 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.Mon Mar 02 21:40:27 CET 2009Hong KongProceedings of the 6th IEEE International Conference on Data Mining (ICDM 06)December907-911TRIAS - An Algorithm for Mining Iceberg Tri-Lattices20062006 FCA OntologyHandbook algorithm analysis concept fca folksonomies folksonomy formal iceberg itegpub lattices myown nepomuk tagging tri triadic trias Mon May 26 11:57:05 CEST 2008Machine Learning#aug#295--122A lattice conceptual clustering system and its application to browsing retrieval241996analysis carpineto clustering concept fca formal information ir retrieval 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 -Fri Mar 28 17:54:33 CET 2008Journal of Web Semantics138-53Discovering Shared Conceptualizations in Folksonomies620082008 FCA OntologyHandbook analysis bibsonomy concept discovering fca folksonomies formal itegpub l3s myown shared triadic Fri Mar 28 16:46:58 CET 2008MannheimBegriffliche Wissensverarbeitung -- Grundfragen und AufgabenB. I. -Wissenschaftsverlag11-25{Plädoyer für eine philosophische Grundlegung der Begrifflichen Wissensverarbeitung}1994FCA OntologyHandbook analysis begriffliche concept conceptual fca formal knowledge processing wissensverarbeitung Fri Mar 28 12:11:30 CET 2008Informatik--Spektrum6357-369{Begriffliche Wissensverarbeitung: Theorie und Praxis}232000FCA OntologyHandbook analysis begriffsanalyse concept conceptual fca formal formale knowledge processing wissensverarbeitung Fri Mar 28 12:11:30 CET 2008MannheimBegriffliche Wissensverarbeitung -- Grundfragen und AufgabenB. I. -Wissenschaftsverlag11-25{Pl�doyer f�r eine philosophische Grundlegung der Begrifflichen Wissensverarbeitung}1994FCA OntologyHandbook analysis begriffliche concept conceptual fca formal knowledge processing wissensverarbeitung Fri Mar 28 12:11:30 CET 2008 Mannheim Beitr{\"a}ge zur Begriffsanalyse 161-211 {Bedeutungen von Begriffsverb{\"a}nden} 1987 FCA OntologyHandbook ag1 analysis begriffsanalyse concept darmstadt fba fca formal formale forschungsgruppe lattices tu Fri Mar 28 12:11:30 CET 2008Manuscript of a lecture given at TH Darmstadt, 60 pagesFebruaryTwo applications of {G}alois graphs in pedagogical research1984FCA OntologyHandbook analysis begriffsanalyse beings concept example fca formal formale living Fri Mar 28 12:11:30 CET 2008Intl. J. Human-Comuter Studies (IJHCS)September3287-325Off to New Shores -- Conceptual Knowledge Discovery and Processing5920032003 Conceptual FCA Knowledge OntologyHandbook Processing analysis concept conceptual discovery fca formal habilitation knowledge myown processing In the last years, the main orientation of Formal Concept Analysis (FCA) has turned from mathematics towards computer science. This article provides a review of this new orientation and analyzes why and how FCA and computer science attracted each other. It discusses FCA as a knowledge representation formalism using five knowledge representation principles provided by Davis, Shrobe, and Szolovits (1993). It then studies how and why mathematics-based researchers got attracted by computer science. We will argue for continuing this trend by integrating the two research areas FCA and Ontology Engineering. The second part of the article discusses three lines of research which witness the new orientation of Formal Concept Analysis: FCA as a conceptual clustering technique and its application for supporting the merging of ontologies; the efficient computation of association rules and the structuring of the results; and the visualization and management of conceptual hierarchies and ontologies including its application in an email management system.Fri Mar 28 12:11:30 CET 2008Journal of Experimental and Theoretical Artificial Intelligence189-216Comparing performance of algorithms for generating concept lattices142002FCA OntologyHandbook algorithm algorithms analysis concept fca formal Fri Mar 28 12:11:30 CET 2008Computer Networks and ISDN Systems1\&2109-117Creating a Web Analysis and Visualization Environment281995Analysis Creating FCA OntologyHandbook Visualization Web analysis concept creating fca formal visualization web Fri Mar 28 12:11:30 CET 2008Translation of: {\it Formale Be\-griffs\-ana\-ly\-se: Mathematische Grundlagen.} Sprin\-ger, Heidelberg 1996.Formal Concept Analysis: Mathematical Foundations1999FCA OntologyHandbook analysis concept fca formal math