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1Datasets
http://www.cs.cmu.edu/~mmcgloho/fec/data/fec_data.html
15 years ago by @folke
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2009
com2cand
compaign
dataset
ecml
pkdd
political
2009com2candcompaigndatasetecmlpkddpolitical
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1Language Technology at the European Commission - Joint Research Centre, Ispra - DGT-TM
multilingual Translation Memory for the Acquis Communautaire (the body of EU law) - a collection of parallel texts (texts and their translation, also referred to as bi-texts) in 22 languages. This is a page for technical users, where you will find a summary of this unique resource and instructions on where to download it
15 years ago by @folke
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2009
ecml
multilinguality
parallel
pkdd
texts
2009ecmlmultilingualityparallelpkddtexts
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2EUROVOC
http://europa.eu/eurovoc/sg/sga_doc/eurovoc_dif%21SERVEUR/menu%21prod%21MENU?langue=DE
15 years ago by @folke
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2009
ecml
eu
multilinugal
pkdd
thesaurus
2009ecmleumultilinugalpkddthesaurus
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1EMM News Brief Real Time Event Map
http://press.jrc.it/geo?type=event&format=html&language=en
15 years ago by @folke
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2009
detection
ecml
event
pkdd
2009detectionecmleventpkdd
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1MedISys
http://medusa.jrc.it/medisys/homeedition/all/home.html
15 years ago by @folke
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2009
MedISys
ecml
media
monitoring
pkdd
2009MedISysecmlmediamonitoringpkdd
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1Europe Media Monitor - EMM
http://emm.jrc.it/overview.html
15 years ago by @folke
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2009
ecml
jrc
media
monitoring
multilinguality
overview
pkdd
2009ecmljrcmediamonitoringmultilingualityoverviewpkdd
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3Identifying the Original Contribution of a Document via Language Modeling
B. Shaparenko, and T. Joachims. Machine Learning and Knowledge Discovery in Databases, (2009)
15 years ago by @folke
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2009
ecml
lda
mining
pkdd
text
2009ecmlldaminingpkddtext
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3Topic Significance Ranking of LDA Generative Models
L. AlSumait, D. Barbará, J. Gentle, and C. Domeniconi. Machine Learning and Knowledge Discovery in Databases, (2009)
15 years ago by @folke
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2009
ecml
generative
lda
mining
model
pkdd
text
2009ecmlgenerativeldaminingmodelpkddtext
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4Latent Dirichlet Allocation for Automatic Document Categorization
I. Bíró, and J. Szabó. Machine Learning and Knowledge Discovery in Databases, (2009)
15 years ago by @folke
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2009
ecml
lda
mining
pkdd
text
2009ecmlldaminingpkddtext
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2Latent Dirichlet Bayesian Co-Clustering
P. Wang, C. Domeniconi, and K. Laskey. Machine Learning and Knowledge Discovery in Databases, (2009)
15 years ago by @folke
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2009
bayesian
clustering
ecml
lda
pkdd
2009bayesianclusteringecmlldapkdd
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1Efficient Pruning Schemes for Distance-Based Outlier Detection
N. Vu, and V. Gopalkrishnan. Machine Learning and Knowledge Discovery in Databases, (2009)
15 years ago by @folke
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2009
clustering
detection
ecml
outlier
pkdd
2009clusteringdetectionecmloutlierpkdd
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2MACs: Multi-Attribute Co-clusters with High Correlation Information
K. Sim, V. Gopalkrishnan, H. Chua, and S. Ng. Machine Learning and Knowledge Discovery in Databases, (2009)
15 years ago by @folke
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2009
clustering
co-clustering
ecml
pkdd
2009clusteringco-clusteringecmlpkdd
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2Soft Margin Trees
J. Díez, J. del Coz, A. Bahamonde, and O. Luaces. Machine Learning and Knowledge Discovery in Databases, (2009)
15 years ago by @folke
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2009
classes
clustering
ecml
metric
pkdd
2009classesclusteringecmlmetricpkdd
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2Binary Decomposition Methods for Multipartite Ranking
J. Fürnkranz, E. Hüllermeier, and S. Vanderlooy. Machine Learning and Knowledge Discovery in Databases, (2009)
15 years ago by @folke
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2009
ecml
graph
multipartite
pkdd
ranking
2009ecmlgraphmultipartitepkddranking
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4Mining Graph Evolution Rules.
M. Berlingerio, F. Bonchi, B. Bringmann, and A. Gionis. ECML/PKDD (1), volume 5781 of Lecture Notes in Computer Science, page 115-130. Springer, (2009)
15 years ago by @folke
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2009
ecml
evolution
generation
graph
pkdd
time
2009ecmlevolutiongenerationgraphpkddtime
(0)
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3RTG: A Recursive Realistic Graph Generator Using Random Typing.
L. Akoglu, and C. Faloutsos. ECML/PKDD (1), volume 5781 of Lecture Notes in Computer Science, page 13-28. Springer, (2009)
15 years ago by @folke
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2009
ecml
generator
graph
law
pkdd
power
properties
2009ecmlgeneratorgraphlawpkddpowerproperties
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2Dynamic Factor Graphs for Time Series Modeling.
P. Mirowski, and Y. LeCun. ECML/PKDD (2), volume 5782 of Lecture Notes in Computer Science, page 128-143. Springer, (2009)
15 years ago by @folke
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2009
ecml
factor
graphs
pkdd
series
time
2009ecmlfactorgraphspkddseriestime
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3Combining Instance-Based Learning and Logistic Regression for Multilabel Classification
W. Cheng, and E. Hüllermeier. Machine Learning and Knowledge Discovery in Databases, (2009)
15 years ago by @folke
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2009
classification
ecml
label
logistic
multi
pkdd
regression
2009classificationecmllabellogisticmultipkddregression
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2Simulated Iterative Classification A New Learning Procedure for Graph Labeling.
F. Maes, S. Peters, L. Denoyer, and P. Gallinari. ECML/PKDD (2), volume 5782 of Lecture Notes in Computer Science, page 47-62. Springer, (2009)
15 years ago by @folke
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2009
classification
ecml
graph
iterative
label
labeling
multi
pkdd
2009classificationecmlgraphiterativelabellabelingmultipkdd
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4Classifier Chains for Multi-label Classification.
J. Read, B. Pfahringer, G. Holmes, and E. Frank. ECML/PKDD (2), volume 5782 of Lecture Notes in Computer Science, page 254-269. Springer, (2009)
15 years ago by @folke
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2009
binary
classification
ecml
label
multi
pkdd
relevance
2009binaryclassificationecmllabelmultipkddrelevance
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BibSonomy

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1Datasets

1Language Technology at the European Commission - Joint Research Centre, Ispra - DGT-TM

2EUROVOC

1EMM News Brief Real Time Event Map

1MedISys

1Europe Media Monitor - EMM

publications (hide)14
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3Identifying the Original Contribution of a Document via Language Modeling

3Topic Significance Ranking of LDA Generative Models

4Latent Dirichlet Allocation for Automatic Document Categorization

2Latent Dirichlet Bayesian Co-Clustering

1Efficient Pruning Schemes for Distance-Based Outlier Detection

2MACs: Multi-Attribute Co-clusters with High Correlation Information

2Soft Margin Trees

2Binary Decomposition Methods for Multipartite Ranking

4Mining Graph Evolution Rules.

3RTG: A Recursive Realistic Graph Generator Using Random Typing.

2Dynamic Factor Graphs for Time Series Modeling.

3Combining Instance-Based Learning and Logistic Regression for Multilabel Classification

2Simulated Iterative Classification A New Learning Procedure for Graph Labeling.

4Classifier Chains for Multi-label Classification.

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