%0 
%0 Conference Proceedings
%A Jäschke, Robert & Rudolph, Sebastian
%D 2013
%T Attribute Exploration on the Web
%E Cellier, Peggy; Distel, Felix & Ganter, Bernhard
%B Contributions to the 11th International Conference on Formal Concept Analysis
%C 
%I 
%V 
%6
%N 
%P 19--34
%& 
%Y Technische Universität Dresden
%S 
%7
%8 May
%9
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%F jaschke2013attribute
%K 2013, acquisition, analysis, attribute, computing, concept, crowdsourcing, data, exploration, fca, formal, human, information, ir, iteg, knowledge, l3s, linked, lod, open, retrieval, search, sparql, web
%X We propose an approach for supporting attribute exploration by web information retrieval, in particular by posing appropriate queries to search engines, crowd sourcing systems, and the linked open data cloud. We discuss underlying general assumptions for this to work and the degree to which these can be taken for granted.
%Z 
%U http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-113133
%+
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%0 
%0 Conference Proceedings
%A 
%D 2005
%T Conceptual Structures: Common Semantics for Sharing Knowledge, 13th International Conference on Conceptual Structures, ICCS 2005, Kassel, Germany, July 17-22, 2005, Proceedings
%E Dau, Frithjof; Mugnier, Marie-Laure & Stumme, Gerd
%B ICCS
%C 
%I Springer
%V 3596
%6
%N 
%P 
%& 
%Y 
%S Lecture Notes in Computer Science
%7
%8 
%9
%? 
%! 
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%@ 3-540-27783-8
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%1 
%2 Publications of Gerd Stumme
%3 proceedings
%4 
%# 
%$ 
%F conf/iccs/2005
%K 2005, Germany, Kassel, analysis, concept, conceptual, conference, fca, formal, graphs, iccs, knowledge, l3s, myown, proceedings, sharing, structures
%X 
%Z 
%U http://www.kde.cs.uni-kassel.de/conf/iccs05
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%0 
%0 Conference Proceedings
%A 
%D 2005
%T Contributions to ICCS 2005
%E Dau, Frithjof; Mugnier, Marie-Laure & Stumme, Gerd
%B Contributions to ICCS 2005
%C Kassel
%I kassel university press
%V 
%6
%N 
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%@ 3-89958-138-5
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%4 
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%$ 
%F dau05contributions
%K 2005, Germany, Kassel, analysis, concept, conceptual, conference, fca, formal, graphs, iccs, knowledge, l3s, myown, proceedings, sharing, structures
%X 
%Z 
%U http://www.kde.cs.uni-kassel.de/conf/iccs05
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%0 
%0 Conference Proceedings
%A Stumme, Gerd
%D 2005
%T Conceptual Knowledge Processing (Invited Talk)
%E Collard, Martine & Cavarero, Jean-Louis
%B Ontologies-based techniques for DataBases and Information Systems
%C Trondheim
%I 
%V 
%6
%N 
%P 5
%& 
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%4 
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%F stumme05conceptual
%K 2005, conceptual, fca, itegpub, knowledge, l3s, myown, ontologies, processing
%X 
%Z 
%U http://www.kde.cs.uni-kassel.de/stumme/papers/2005/stumme2005some_slides.pdf
%+
%^

%0 
%0 Book Section
%A Cimiano, Philipp; Hotho, Andreas; Stumme, Gerd & Tane, Julien
%D 2004
%T Conceptual Knowledge Processing with Formal Concept
                   Analysis and Ontologies
%E Eklund, Peter
%B Concept Lattices
%C Berlin/Heidelberg
%I Springer
%V 2961
%6
%N 
%P 189--207
%& 
%Y 
%S Lecture Notes in Computer Science
%7 
%8 
%9 
%? 
%! 
%Z 
%@ 978-3-540-21043-6
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%2 
%3 incollection
%4 
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%F cimiano2004conceptual
%K 2004, citedBy:doerfel2012publication, fca, icfca, itegpub, knowledge, l3s, myown, processing
%X 
%Z 
%U http://dx.doi.org/10.1007/978-3-540-24651-0_18
%+
%^

%0 
%0 Conference Proceedings
%A Cimiano, Philipp; Hotho, Andreas; Stumme, Gerd & Tane, Julien
%D 2004
%T Conceptual Knowledge Processing with Formal Concept Analysis and Ontologies
%E Eklund, Peter
%B Concept Lattices
%C Heidelberg
%I Springer
%V 2961
%6
%N 
%P 189-207
%& 
%Y Second International Conference on Formal Concept Analysis, ICFCA 2004
%S LNAI
%7
%8 
%9
%? 
%! 
%Z 
%@ 3-540-23258-3
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%3 inproceedings
%4 
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%$ 
%F cimiano2004concept
%K 2004, ckp, conceptual, fca, itegpub, knowledge, l3s, myown, ontologies, processing
%X 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.
%Z 
%U http://www.kde.cs.uni-kassel.de/stumme/papers/2004/cimiano2004concept.pdf
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%^

%0 
%0 Journal Article
%A Hereth, Joachim; Stumme, Gerd; Wille, Rudolf & Wille, Uta
%D 2003
%T Conceptual Knowledge Discovery - a Human-Centered Approach
%E 
%B Journal of Applied Artificial Intelligence (AAI)
%C 
%I 
%V 17
%6
%N 3
%P 281-301
%& 
%Y 
%S 
%7
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%F hereth03conceptual
%K 2003, analysis, concept, conceptual, discovery, fca, formal, human, kdd, knowledge, myown
%X 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.
%Z 
%U http://www.kde.cs.uni-kassel.de/stumme/papers/2003/hereth2003conceptual.pdf
%+
%^

%0 
%0 Report
%A Hotho, Andreas; Staab, Steffen & Stumme, Gerd
%D 2003
%T Text Clustering Based on Background Knowledge
%E 
%B 
%C 
%I University of Karlsruhe, Institute AIFB
%V 
%6
%N 
%P 
%& 
%Y 
%S 
%7
%8 
%9 Technical Report 
%? 
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%3 techreport
%4 
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%$ 
%F hotho03textclustering
%K 2003, analysis, background, clustering, concept, fca, formal, knowledge, myown, ontologies, semantic, text, web
%X Text document clustering plays an important role in providing intuitive
navigation and browsing mechanisms by organizing large amounts of information
into a small number of meaningful clusters. Standard partitional or agglomerative
clustering methods efficiently compute results to this end.
However, the bag of words representation used for these clustering methods is often
unsatisfactory as it ignores relationships between important terms that do not
co-occur literally. Also, it is mostly left to the user to find out why a particular partitioning
has been achieved, because it is only specified extensionally. In order to
deal with the two problems, we integrate background knowledge into the process of
clustering text documents.
First, we preprocess the texts, enriching their representations by background knowledge
provided in a core ontology — in our application Wordnet. Then, we cluster
the documents by a partitional algorithm. Our experimental evaluation on Reuters
newsfeeds compares clustering results with pre-categorizations of news. In the experiments,
improvements of results by background knowledge compared to the baseline
can be shown for many interesting tasks.
Second, the clustering partitions the large number of documents to a relatively small
number of clusters, which may then be analyzed by conceptual clustering. In our approach,
we applied Formal Concept Analysis. Conceptual clustering techniques are
known to be too slow for directly clustering several hundreds of documents, but they
give an intensional account of cluster results. They allow for a concise description
of commonalities and distinctions of different clusters. With background knowledge
they even find abstractions like “food” (vs. specializations like “beef” or “corn”).
Thus, in our approach, partitional clustering reduces first the size of the problem
such that it becomes tractable for conceptual clustering, which then facilitates the
understanding of the results.
%Z 
%U http://www.kde.cs.uni-kassel.de/stumme/papers/2003/hotho2003text.pdf
%+
%^

%0 
%0 Book Section
%A Stumme, G.
%D 2002
%T Using Ontologies and Formal Concept Analysis for Organizing Business Knowledge
%E Becker, J. & Knackstedt, R.
%B Wissensmanagement mit Referenzmodellen -- Konzepte für die Anwendungssystem- und Organisationsgestaltung
%C Heidelberg
%I Physica
%V 
%6
%N 
%P 163-174
%& 
%Y 
%S 
%7 
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%3 incollection
%4 
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%F stumme02using
%K 2002, analysis, business, concept, fca, formal, knowledge, management, myown, ontologies, semantic, web, wissensmanagement
%X 
%Z 
%U http://www.kde.cs.uni-kassel.de/stumme/papers/2001/REFMOD01.ps
%+
%^

%0 
%0 Conference Proceedings
%A 
%D 2000
%T Begriffliche Wissensverarbeitung -- Methoden und Anwendungen
%E Stumme, Gerd & Wille, Rudolf
%B 
%C Heidelberg
%I Springer
%V 
%6
%N 
%P 
%& 
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%S 
%7
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%3 proceedings
%4 
%# 
%$ 
%F stumme00begriffliche
%K 2000, FCA, OntologyHandbook, analysis, begriffliche, concept, conceptual, engineering, fca, formal, knowledge, myown, processing, wissensverarbeitung
%X 
%Z 
%U http://www.springer.com/dal/home/generic/search/results?SGWID=1-40109-22-2058937-0
%+
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%0 
%0 Report
%A Stumme, G.
%D 1999
%T Conceptual Knowledge Discovery with Frequent Concept Lattices
%E 
%B 
%C 
%I TU Darmstadt
%V 
%6
%N 
%P 
%& 
%Y 
%S 
%7
%8 
%9 {FB}4-{P}reprint 2043
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%3 techreport
%4 
%# 
%$ 
%F stumme99conceptualknowledge
%K 1999, analysis, association, closed, concept, condensed, data, discovery, fca, formal, frequent, iceberg, itemsets, kdd, knowledge, lattices, mining, myown, representations, rule, rules
%X 
%Z 
%U http://www.kde.cs.uni-kassel.de/stumme/papers/1999/P2043.pdf
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%0 
%0 Conference Proceedings
%A Stumme, Gerd
%D 1999
%T Acquiring Expert Knowledge for the Design of Conceptual Information Systems
%E Fensel, D. & Studer, R.
%B Knowledge Acquisition, Modeling, and Management. Proc. 11th European
%C Heidelberg
%I Springer
%V 1621
%6
%N 
%P 275-290
%& 
%Y 
%S LNAI
%7
%8 
%9
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%4 
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%F Stumme1999acquiring
%K 1999, acquisition, analysis, attribute, concept, conceptual, exploration, fca, formal, information, knowledge, lattices, myown, systems
%X 
%Z 
%U http://www.kde.cs.uni-kassel.de/stumme/papers/1999/P1997-EKAW99.pdf
%+
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%0 
%0 Conference Proceedings
%A Stumme, Gerd
%D 1998
%T Distributive Concept Exploration - A Knowledge Acquisition Tool in Formal Concept Analysis
%E Herzog, O. & Günter, A.
%B KI-98: Advances in Artificial Intelligence. Proc. 22. Jahrestagung
%C Heidelberg
%I Springer
%V 1504
%6
%N 
%P 117-128
%& 
%Y 
%S LNAI
%7
%8 
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%3 inproceedings
%4 
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%$ 
%F stumme98knowledgeacquisition
%K 1998, acquisition, analysis, attribute, concept, exploration, fca, formal, knowledge, myown
%X 
%Z 
%U http://www.kde.cs.uni-kassel.de/stumme/papers/1998/KI98.pdf
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%0 
%0 Journal Article
%A Stumme, Gerd
%D 1998
%T Knowledge, Logic, Information. Conference Report.
%E 
%B Zeitschrift für Semiotik
%C 
%I 
%V 20
%6
%N 3-4
%P 424
%& 
%Y 
%S 
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%3 article
%4 
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%F stumme98knowledge
%K 1998, analysis, concept, conference, fca, formal, information, knowledge, logic, myown, report
%X 
%Z 
%U 
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%0 
%0 Conference Proceedings
%A Stumme, Gerd
%D 1997
%T Concept Exploration - A Tool for Creating and Exploring Conceptual Hierarchies
%E Lukose, D.; Delugach, H.; Keeler, M.; Searle, L. & Sowa, J. F.
%B Conceptual Structures: Fulfilling  Peirce's Dream. Proc. ICCS'97
%C Berlin
%I Springer
%V 1257
%6
%N 
%P 
%& 
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%S LNAI
%7
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%4 
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%F stumme97tool
%K 1997, Conceptual, OntologyHandbook, acquisition, analysis, attribute, concept, conceptual, exploration, fca, formal, hierarchies, knowledge, lattices, myown
%X 
%Z 
%U http://www.kde.cs.uni-kassel.de/stumme/papers/1997/P1905-ICCS97.pdf
%+
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%0 
%0 Book
%A Stumme, Gerd
%D 1997
%T Concept Exploration -- Knowledge Acquisition in Knowledge Systems. 
%E 
%B 
%C Aachen
%I Shaker
%V 
%6
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%F stumme97conceptexploration
%K 1997, acquisition, analysis, attribute, concept, conceptual, exploration, fca, formal, knowledge, myown, systems
%X 
%Z 
%U http://www.shaker.de/Online-Gesamtkatalog/details.asp?ISBN=3-8265-2930-8
%+
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%0 
%0 Conference Proceedings
%A Stumme, Gerd
%D 1996
%T Attribute Exploration with Background Implications and Exceptions
%E Bock, H.-H. & Polasek, W.
%B Data Analysis  and  Information  Systems. Statistical and Conceptual approaches. Proc. GfKl'95. Studies in Classification, Data Analysis, and Knowledge Organization 7
%C Heidelberg
%I Springer
%V 
%6
%N 
%P 457-469
%& 
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%4 
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%F stumme96attribute
%K 1996, acquisition, analysis, attribute, background, concept, exploration, fca, formal, implications, knowledge, lattices, myown
%X 
%Z 
%U http://www.kde.cs.uni-kassel.de/stumme/papers/1995/P1781-GfKl95.pdf
%+
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%0 
%0 Conference Proceedings
%A Wille, Rudolf
%D 1994
%T Plädoyer für eine philosophische Grundlegung der Begrifflichen Wissensverarbeitung
%E Wille, R. & Zickwolff, M.
%B Begriffliche Wissensverarbeitung -- Grundfragen und Aufgaben
%C Mannheim
%I B. I. -Wissenschaftsverlag
%V 
%6
%N 
%P 11-25
%& 
%Y 
%S 
%7
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%1 
%2 fca
%3 inproceedings
%4 
%# 
%$ 
%F wille94plaedoyer
%K FCA, OntologyHandbook, analysis, begriffliche, concept, conceptual, fca, formal, knowledge, processing, wissensverarbeitung
%X 
%Z 
%U 
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