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4A Repository for Formal Contexts
T. Hanika, and R. Jäschke. Conceptual Knowledge Structures, 14914, page 182--197. Cham, Springer Nature Switzerland, (2024)
9 months ago by @jaeschke
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2024
analysis
concept
data
dataset
fca
formal
myown
repository
research
2024analysisconceptdatadatasetfcaformalmyownrepositoryresearch
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6Exploring Scale-Measures of Data Sets
T. Hanika, and J. Hirth. (2021)cite arxiv:2102.02576Comment: 16 pages, 5 figures.
4 years ago by @hirth
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data
fca
long-version
preprocessing
scale-measure
scaling
datafcalong-versionpreprocessingscale-measurescaling
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6Exploring Scale-Measures of Data Sets
T. Hanika, and J. Hirth. (2021)cite arxiv:2102.02576Comment: 16 pages, 5 figures.
4 years ago by @citationstyle
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data
escapetest
fca
preprint
preprocessing
publist
scale-measure
scaling
someid:test
dataescapetestfcapreprintpreprocessingpublistscale-measurescalingsomeid:test
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1Intrinsic Dimension of Geometric Data Sets
T. Hanika, F. Schneider, and G. Stumme. Accepted for publication in: Tohoku Mathematical Journal, (2020)cite arxiv:1801.07985Comment: v2: completely rewritten 28 pages, 3 figures, 2 tables.
4 years ago by @stumme
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2020
data
fca
geometry
itegpub
kde
kdepub
mm-space
myown
publist
2020datafcageometryitegpubkdekdepubmm-spacemyownpublist
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1Intrinsic Dimension of Geometric Data Sets
T. Hanika, F. Schneider, and G. Stumme. (2018)cite arxiv:1801.07985Comment: v2: completely rewritten 28 pages, 3 figures, 2 tables.
6 years ago by @stumme
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2018
data
fca
geometry
itegpub
kde
kdepub
mm-space
myown
2018datafcageometryitegpubkdekdepubmm-spacemyown
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2Intrinsic dimension of concept lattices
T. Hanika, F. Schneider, and G. Stumme. CoRR, (2018)cite arxiv:1801.07985Comment: 13 pages, 3 figures.
6 years ago by @stumme
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2018
curse
data
dimension
fca
geometric
intrinsic
itegpub
kde
kdepub
myown
preprint
publist
2018cursedatadimensionfcageometricintrinsicitegpubkdekdepubmyownpreprintpublist
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2MinerLSD: Efficient Local Pattern Mining on Attributed Graphs
M. Atzmueller, H. Soldano, G. Santini, and D. Bouthinon. Proc. Proc. 2018 IEEE International Conference on Data Mining Workshops (ICDMW), ((accepted) 2018)
7 years ago by @atzmueller
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2018
abstraction
analysis
attributed
complex
concept
core
data
fca
formal
graph
local
mining
myown
network
pattern
2018abstractionanalysisattributedcomplexconceptcoredatafcaformalgraphlocalminingmyownnetworkpattern
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6Attribute Exploration on the Web
R. Jäschke, and S. Rudolph. Contributions to the 11th International Conference on Formal Concept Analysis, page 19--34. Technische Universität Dresden, (May 2013)
10 years ago by @kde-alumni
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2013
acquisition
analysis
attribute
computing
concept
crowdsourcing
data
exploration
fca
formal
human
information
ir
knowledge
linked
lod
myown
open
retrieval
search
sparql
web
2013acquisitionanalysisattributecomputingconceptcrowdsourcingdataexplorationfcaformalhumaninformationirknowledgelinkedlodmyownopenretrievalsearchsparqlweb
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6Attribute Exploration on the Web
R. Jäschke, and S. Rudolph. Contributions to the 11th International Conference on Formal Concept Analysis, page 19--34. Technische Universität Dresden, (May 2013)
10 years ago by @kdepublication
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2013
acquisition
analysis
attribute
computing
concept
crowdsourcing
data
exploration
fca
formal
human
information
ir
iteg
kde
knowledge
l3s
linked
lod
mykopie
myown
open
retrieval
search
sparql
web
2013acquisitionanalysisattributecomputingconceptcrowdsourcingdataexplorationfcaformalhumaninformationiritegkdeknowledgel3slinkedlodmykopiemyownopenretrievalsearchsparqlweb
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6Attribute Exploration on the Web
R. Jäschke, and S. Rudolph. Contributions to the 11th International Conference on Formal Concept Analysis, page 19--34. Technische Universität Dresden, (May 2013)
12 years ago by @stumme
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2013
acquisition
analysis
attribute
computing
concept
crowdsourcing
data
exploration
fca
formal
human
information
ir
iteg
knowledge
l3s
linked
lod
open
retrieval
search
sparql
web
2013acquisitionanalysisattributecomputingconceptcrowdsourcingdataexplorationfcaformalhumaninformationiritegknowledgel3slinkedlodopenretrievalsearchsparqlweb
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6Attribute Exploration on the Web
R. Jäschke, and S. Rudolph. Contributions to the 11th International Conference on Formal Concept Analysis, page 19--34. Technische Universität Dresden, (May 2013)
12 years ago by @jaeschke
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2013
acquisition
analysis
attribute
computing
concept
crowdsourcing
data
exploration
fca
formal
human
information
ir
knowledge
linked
lod
myown
open
retrieval
search
sparql
web
2013acquisitionanalysisattributecomputingconceptcrowdsourcingdataexplorationfcaformalhumaninformationirknowledgelinkedlodmyownopenretrievalsearchsparqlweb
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2What Can Formal Concept Analysis Do for Data Warehouses?.
R. Missaoui, and L. Kwuida. ICFCA, volume 5548 of Lecture Notes in Computer Science, page 58-65. Springer, (2009)
15 years ago by @obj
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data
fca
warehouses
datafcawarehouses
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7Efficient Data Mining Based on Formal Concept Analysis
G. Stumme. Database and Expert Systems Applications. Proc. DEXA 2002, volume 2453 of LNCS, page 534-546. Heidelberg, Springer, (2002)
15 years ago by @obj
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data
fca
kdd
mining
rules
datafcakddminingrules
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4Mining Frequent Patterns with Counting Inference.
Y. Bastide, R. Taouil, N. Pasquier, G. Stumme, and L. Lakhal. SIGKDD Explorations, Special Issue on Scalable Algorithms, 2 (2): 71-80 (2000)
16 years ago by @stumme
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2000
FCA
OntologyHandbook
analys
association
closed
concept
condensed
data
discovery
fca
formal
frequent
itemsets
kdd
knowledge
mining
myown
representation
representations
rule
rules
2000FCAOntologyHandbookanalysassociationclosedconceptcondenseddatadiscoveryfcaformalfrequentitemsetskddknowledgeminingmyownrepresentationrepresentationsrulerules
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6Mining Minimal Non-Redundant Association Rules Using Frequent Closed Itemsets
Y. Bastide, N. Pasquier, R. Taouil, G. Stumme, and L. Lakhal. Computational Logic --- CL 2000 Proc. CL'00, volume 1861 of LNAI, Heidelberg, Springer, (2000)
16 years ago by @stumme
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2000
analys
association
closed
concept
condensed
data
discovery
fca
formal
frequent
itemsets
kdd
knowledge
mining
myown
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rule
rules
2000analysassociationclosedconceptcondenseddatadiscoveryfcaformalfrequentitemsetskddknowledgeminingmyownrepresentationrepresentationsrulerules
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7Efficient Data Mining Based on Formal Concept Analysis
G. Stumme. Database and Expert Systems Applications. Proc. DEXA 2002, volume 2453 of LNCS, page 534-546. Heidelberg, Springer, (2002)
16 years ago by @stumme
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2002
association
closed
condensed
data
discovery
fca
itemsets
kdd
knowledge
mining
myown
representations
rules
2002associationclosedcondenseddatadiscoveryfcaitemsetskddknowledgeminingmyownrepresentationsrules
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6Efficient Mining of Association Rules Based on Formal Concept Analysis
L. Lakhal, and G. Stumme. volume 3626 of LNAI, page 180-195. Springer, Heidelberg, (2005)
16 years ago by @stumme
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2005
analysis
association
book
closed
concept
condensed
data
discovery
fca
formal
itegpub
itemsets
kdd
knowledge
l3s
mining
myown
representations
rules
2005analysisassociationbookclosedconceptcondenseddatadiscoveryfcaformalitegpubitemsetskddknowledgel3sminingmyownrepresentationsrules
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5ToscanaJ: An Open Source Tool for Qualitative Data Analysis
P. Becker, J. Hereth, and G. Stumme. Advances in Formal Concept Analysis for Knowledge Discovery in Databases., page 1-2. Lyon, France, (July 2002)
17 years ago by @cschenk
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analysis
concepts
data
discovery
fca
kdd
knowledge
paper
qualitative
read:2008
sourceforge
stumme
tool
toscanaj
analysisconceptsdatadiscoveryfcakddknowledgepaperqualitativeread:2008sourceforgestummetooltoscanaj
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2Formal Concept Analysis for the Identification of Combinatorial Biomarkers in Breast Cancer.
S. Motameny, B. Versmold, and R. Schmutzler. ICFCA, volume 4933 of Lecture Notes in Computer Science, page 229-240. Springer, (2008)
17 years ago by @jwollbold
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FCA
biology
data
expression
gene
FCAbiologydataexpressiongene
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4A Repository for Formal Contexts

6Exploring Scale-Measures of Data Sets

6Exploring Scale-Measures of Data Sets

1Intrinsic Dimension of Geometric Data Sets

1Intrinsic Dimension of Geometric Data Sets

2Intrinsic dimension of concept lattices

2MinerLSD: Efficient Local Pattern Mining on Attributed Graphs

6Attribute Exploration on the Web

6Attribute Exploration on the Web

6Attribute Exploration on the Web

6Attribute Exploration on the Web

2What Can Formal Concept Analysis Do for Data Warehouses?.

7Efficient Data Mining Based on Formal Concept Analysis

4Mining Frequent Patterns with Counting Inference.

6Mining Minimal Non-Redundant Association Rules Using Frequent Closed Itemsets

7Efficient Data Mining Based on Formal Concept Analysis

6Efficient Mining of Association Rules Based on Formal Concept Analysis

5ToscanaJ: An Open Source Tool for Qualitative Data Analysis

2Formal Concept Analysis for the Identification of Combinatorial Biomarkers in Breast Cancer.

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