PUMA publications for /user/stumme/FCA%20itegpubMon Mar 18 14:06:44 CET 2013Berlin/HeidelbergICFCA 201277--95Lecture Notes in Artificial IntelligencePublication Analysis of the Formal Concept Analysis Community727820122012 analysis community concept fca home info20pub itegpub l3s myown scientometrics 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.
Mon Mar 18 14:06:44 CET 2013Berlin/HeidelbergConcept Lattices189--207Lecture Notes in Computer ScienceConceptual Knowledge Processing with Formal Concept
Analysis and Ontologies296120042004 citedBy:doerfel2012publication fca icfca itegpub knowledge l3s myown processing Mon Mar 18 14:06:44 CET 2013Amsterdam, The Netherlands, The NetherlandsData \& Knowledge Engineering2189--222Computing iceberg concept lattices with TITANIC422002citedBy:doerfel2012publication fca icfca itegpub l3s myown titanic 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.Wed Apr 07 13:54:41 CEST 2010HeidelbergConceptual Structures at Work: 12th International Conference on Conceptual Structures (ICCS 2004)109-125LNCSIceberg Query Lattices for Datalog312720042004 analysis concept context datalog families family fca formal iceberg itegpub l3s lattices myown pcf power queries query Wed Apr 07 13:54:41 CEST 2010Journal of Web Semantics138-53Discovering Shared Conceptualizations in Folksonomies620082008 FCA OntologyHandbook analysis bibsonomy concept discovering fca folksonomies formal itegpub l3s myown shared triadic Wed Apr 07 13:54:41 CEST 2010HeidelbergProc. 3rd Intl. Conf. on Formal Concept Analysis315-328Lecture Notes in Computer ScienceA Finite State Model for On-Line Analytical Processing in
Triadic Contexts340320052005 fca folksonomies itegpub l3s myown olap triadic Wed Apr 07 13:54:41 CEST 2010Proc. 13th International World Wide Web Conference (WWW 2004)1-10Semantic resource management for the web: an e-learning application20042004 application courseware crawler e-learning eLearning edutella fca itegpub l3s learning myown p2p semantic watchdog web Wed Apr 07 13:54:41 CEST 2010HeidelbergConcept Lattices189-207LNAIConceptual Knowledge Processing with Formal Concept Analysis and Ontologies296120042004 ckp conceptual fca itegpub knowledge l3s myown ontologies processing Among many other knowledge representations formalisms, Ontologies
and Formal Concept Analysis (FCA) aim at modeling 'concepts'. We
discuss how these two formalisms may complement another from an
application point of view. In particular, we will see how FCA can
be used to support Ontology Engineering, and how ontologies can be
exploited in FCA applications. The interplay of FCA and ontologies
is studied along the life cycle of an ontology:
(i) FCA can support the building of the ontology as a
learning technique.
(ii) The established ontology can be analyzed and navigated by
using techniques of FCA.
(iii) Last but not least, the ontology may be used to improve an FCA
application.Wed Apr 07 13:54:41 CEST 2010TrondheimOntologies-based techniques for DataBases and Information Systems5Conceptual Knowledge Processing (Invited Talk)20052005 conceptual fca itegpub knowledge l3s myown ontologies processing Wed Apr 07 13:54:41 CEST 2010Journal Intelligent Information Systems (JIIS)129-60Generating a Condensed Representation for Association Rules2420052005 OntologyHandbook analysis association closed concept condensed data discovery fca formal itegpub itemset kdd knowledge l3s mining myown representations rule rules sets Wed Apr 07 13:54:41 CEST 2010BanffProc. WWW2007 Workshop ``Tagging and Metadata for Social Information Organization''mayNetwork Properties of Folksonomies20072007 emergent fca folksonomy folksononomies itegpub l3s myown semantics smallworld sna socialnetwork 8Wed Apr 07 13:54:41 CEST 2010Proc. 3rd Intl. Conf. on Formal Concept Analysis315-328LNCSA Finite State Model for On-Line Analytical Processing in Triadic
Contexts.340320052005 FCA OntologyHandbook context fca itegpub myown olap triadic Wed Apr 07 13:54:41 CEST 2010HeidelbergLNAIFormal Concept Analysis -- Foundations and Applications362620052005 FCA OntologyHandbook itegpub myown Wed Apr 07 13:54:41 CEST 2010Berlin, HeidelbergData Science and Classification: Proc. of the 10th IFCS Conf.261--270Studies in Classification, Data Analysis, and Knowledge OrganizationMining Association Rules in Folksonomies20062006 FCA OntologyHandbook association folksonomy itegpub myown rule Wed Apr 07 13:54:41 CEST 2010AI Communications Journal, Special Issue on ``Network Analysis in Natural Sciences and Engineering''4245-262Network Properties of Folksonomies2020072007 emergent fca folksonomies folksonomy itegpub l3s myown network semantics seminar2009 tagorapub Wed Apr 07 13:54:41 CEST 2010HeidelbergFormal 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.Thu Jul 02 00:08:08 CEST 2009HeidelbergThe Semantic Web: Research and ApplicationsJune411-426LNAIInformation Retrieval in Folksonomies: Search and Ranking401120062006 FCA IR OntologyHandbook folkrank folksonomy information informationretrieval itegpub mimose myown pagerank ranking retrieval 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