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1A Novel Approach for Identification and Linking of Short Quotations in Scholarly Texts and Literary Works
F. Arnold, and R. Jäschke. Journal of Computational Literary Studies, (2023)
2 years ago by @jaeschke
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2023
citation
dh
digital
humanities
identification
jcls
myown
nlp
reuse
text
2023citationdhdigitalhumanitiesidentificationjclsmyownnlpreusetext
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1Lotte and Annette: A Framework for Finding and Exploring Key Passages in Literary Works
F. Arnold, and R. Jäschke. Proceedings of the Workshop on Natural Language Processing for Digital Humanities at ICON 2021, page 55--63. NLP Association of India, (2021)
3 years ago by @jaeschke
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2021
annette
dh
digital
humanities
lotte
myown
nlp
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text
2021annettedhdigitalhumanitieslottemyownnlpreusetext
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4Data Preparation for Big Data Analytics: Methods & Experiences
A. Schmidt, M. Atzmueller, and M. Hollender. Enterprise Big Data Engineering, Analytics, and Management, IGI Global, Hershey, PA, USA, (2016)
6 years ago by @kde-alumni
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2016
analytics
big
data
detection
discovery
exceptional
exceptionality
extraction
feepub
information
itegpub
knowledge
local
mining
model
myown
nlp
preparation
preprocessing
subgroup
text
2016analyticsbigdatadetectiondiscoveryexceptionalexceptionalityextractionfeepubinformationitegpubknowledgelocalminingmodelmyownnlppreparationpreprocessingsubgrouptext
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2Enterprise Big Data Engineering, Analytics and Management
M. Atzmueller, S. Oussena, and T. Roth-Berghofer (Eds.) IGI Global, Hershey, PA, USA, (2016)
6 years ago by @kde-alumni
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2016
analysis
analytics
big
data
discovery
engineering
itegpub
knowledge
language
management
mining
myown
natural
network
processing
social
text
2016analysisanalyticsbigdatadiscoveryengineeringitegpubknowledgelanguagemanagementminingmyownnaturalnetworkprocessingsocialtext
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3BISHOP – Big Data Driven Self-Learning Support for High-performance Ontology Population
D. Knoell, M. Atzmueller, C. Rieder, and K. Scherer. Proc. LWA 2016 (FGWM Special Track), Potsdam, Germany, University of Potsdam, (2016)
6 years ago by @kde-alumni
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2016
big
data
discovery
extraction
information
itegpub
mining
myown
ontology
population
text
2016bigdatadiscoveryextractioninformationitegpubminingmyownontologypopulationtext
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2Data Mining
M. Atzmueller. Applied Natural Language Processing and Content Analysis: Advances in Identification, Investigation and Resolution., IGI Global, (2011)
6 years ago by @kde-alumni
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2011
data
discovery
itegpub
knowledge
mining
myown
nlp
text
2011datadiscoveryitegpubknowledgeminingmyownnlptext
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4Boosting for Text Classification with Semantic Features (reprint)
S. Bloehdorn, and A. Hotho. Proceedings of the Workshop on Text-based Information Retrieval (TIR-04) at the 27th German Conference on Artificial Intelligence, (September 2004)
8 years ago by @kde-alumni
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2004
boosting
classification
myown
ontology
text
2004boostingclassificationmyownontologytext
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17A Brief Survey of Text Mining
A. Hotho, A. Nürnberger, and G. Paaß. LDV Forum - GLDV Journal for Computational Linguistics and Language Technology, 20 (1): 19-62 (May 2005)
8 years ago by @kde-alumni
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2005
SumSchool06
mining
myown
ontology
overview
survey
text
tm
2005SumSchool06miningmyownontologyoverviewsurveytexttm
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6Text Clustering Based on Good Aggregations
A. Hotho, A. Maedche, and S. Staab. Künstliche Intelligenz (KI), 16 (4): 48-54 (2002)
8 years ago by @kde-alumni
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2002
SumSchool06
clustering
myown
ontology
text
2002SumSchool06clusteringmyownontologytext
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4On Knowledgeable Unsupervised Text Mining
A. Hotho, A. Maedche, S. Staab, and V. Zacharias. Proc. of Text Mining Workshop, (2002)
8 years ago by @kde-alumni
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2002
mining
myown
text
2002miningmyowntext
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9Prediction of Happy Endings in German Novels
A. Zehe, M. Becker, L. Hettinger, A. Hotho, I. Reger, and F. Jannidis. DMNLP@PKDD/ECML, volume 1646 of CEUR Workshop Proceedings, page 9-16. CEUR-WS.org, (2016)
8 years ago by @hotho
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2016
endings
german
happy
kallimachos
mining
myown
novels
prediction
text
2016endingsgermanhappykallimachosminingmyownnovelspredictiontext
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8Genre classification on German novels
L. Hettinger, M. Becker, I. Reger, F. Jannidis, and A. Hotho. Proceedings of the 12th International Workshop on Text-based Information Retrieval, (2015)
8 years ago by @hotho
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2015
classification
genre
kallimachos
lda
mining
myown
text
2015classificationgenrekallimachosldaminingmyowntext
(0)
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3BISHOP – Big Data Driven Self-Learning Support for High-performance Ontology Population
D. Knoell, M. Atzmueller, C. Rieder, and K. Scherer. Proc. LWA 2016 (FGWM Special Track), Potsdam, Germany, University of Potsdam, (2016)
8 years ago by @atzmueller
show all tags
2016
big
data
discovery
extraction
information
itegpub
mining
myown
ontology
population
text
2016bigdatadiscoveryextractioninformationitegpubminingmyownontologypopulationtext
(0)
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2Enterprise Big Data Engineering, Analytics and Management
M. Atzmueller, S. Oussena, and T. Roth-Berghofer (Eds.) IGI Global, Hershey, PA, USA, (2016)
9 years ago by @atzmueller
show all tags
2016
analysis
analytics
big
data
discovery
engineering
itegpub
knowledge
language
management
mining
myown
natural
network
processing
social
text
2016analysisanalyticsbigdatadiscoveryengineeringitegpubknowledgelanguagemanagementminingmyownnaturalnetworkprocessingsocialtext
(0)
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4Data Preparation for Big Data Analytics: Methods & Experiences
A. Schmidt, M. Atzmueller, and M. Hollender. Enterprise Big Data Engineering, Analytics, and Management, IGI Global, Hershey, PA, USA, (2016)
9 years ago by @atzmueller
show all tags
2016
analytics
big
data
detection
discovery
exceptional
exceptionality
extraction
feepub
information
itegpub
knowledge
local
mining
model
myown
nlp
preparation
preprocessing
subgroup
text
2016analyticsbigdatadetectiondiscoveryexceptionalexceptionalityextractionfeepubinformationitegpubknowledgelocalminingmodelmyownnlppreparationpreprocessingsubgrouptext
(0)
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17A Brief Survey of Text Mining
A. Hotho, A. Nürnberger, and G. Paaß. LDV Forum - GLDV Journal for Computational Linguistics and Language Technology, 20 (1): 19-62 (May 2005)
9 years ago by @dmir
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2005
SumSchool06
from:hotho
mining
myown
ontology
overview
survey
text
tm
2005SumSchool06from:hothominingmyownontologyoverviewsurveytexttm
(0)
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29Learning Concept Hierarchies from Text Corpora using Formal Concept Analysis
P. Cimiano, A. Hotho, and S. Staab. Journal on Artificial Intelligence Research, (2005)
9 years ago by @dmir
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2005
fca
folksonomy
from:hotho
hierarchies
hierarchy
learning
myown
ontologies
semantic
text
2005fcafolksonomyfrom:hothohierarchieshierarchylearningmyownontologiessemantictext
(0)
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16Clustern mit Hintergrundwissen
A. Hotho. Diski Akademische Verlagsgesellschaft Aka GmbH, Berlin, (2004)
9 years ago by @dmir
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2004
SumSchool06
clustern
from:hotho
hintergrundwissen
myown
ontology
text
2004SumSchool06clusternfrom:hothohintergrundwissenmyownontologytext
(0)
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4On Knowledgeable Unsupervised Text Mining
A. Hotho, A. Maedche, S. Staab, and V. Zacharias. Proc. of Text Mining Workshop, (2002)
9 years ago by @dmir
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2002
from:hotho
mining
myown
text
2002from:hothominingmyowntext
(0)
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4Combining Data-Driven and Semantic Approaches for Text Mining.
S. Bloehdorn, S. Blohm, P. Cimiano, E. Giesbrecht, A. Hotho, U. Lösch, A. Mädche, E. Mönch, P. Sorg, S. Staab and 1 other author(s). Foundations for the Web of Information and Services, page 115-142. Springer, (2011)
9 years ago by @dmir
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2011
data
from:hotho
mining
myown
semantic
text
2011datafrom:hothominingmyownsemantictext
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1A Novel Approach for Identification and Linking of Short Quotations in Scholarly Texts and Literary Works

1Lotte and Annette: A Framework for Finding and Exploring Key Passages in Literary Works

4Data Preparation for Big Data Analytics: Methods & Experiences

2Enterprise Big Data Engineering, Analytics and Management

3BISHOP – Big Data Driven Self-Learning Support for High-performance Ontology Population

2Data Mining

4Boosting for Text Classification with Semantic Features (reprint)

17A Brief Survey of Text Mining

6Text Clustering Based on Good Aggregations

4On Knowledgeable Unsupervised Text Mining

9Prediction of Happy Endings in German Novels

8Genre classification on German novels

3BISHOP – Big Data Driven Self-Learning Support for High-performance Ontology Population

2Enterprise Big Data Engineering, Analytics and Management

4Data Preparation for Big Data Analytics: Methods & Experiences

17A Brief Survey of Text Mining

29Learning Concept Hierarchies from Text Corpora using Formal Concept Analysis

16Clustern mit Hintergrundwissen

4On Knowledgeable Unsupervised Text Mining

4Combining Data-Driven and Semantic Approaches for Text Mining.

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