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Active Learning Survey
» JULIE Lab
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» Dr. Katrin Tomanek
» Research
Research
Research Interests
Machine Learning (especially graphical models)
Active Learning (especially efficient approaches to real-world learning and annotation problems)
Named Entity Recognition and Normalization
Natural Language Processing of biomedical texts
NLP Frameworks (i.e. UIMA, GATE)
Annotation "as a science" (modelling annotation costs and the annotation process, cost-conscious methods to training material creation)
Application of above methods for large-scale information extraction and data mining
Research Projects Involved
EU Support Action Project
CALBC
EU Strep Project
BOOTStrep
(terminated)
BMBF e-science Project
StemNet
(terminated)
EU Network of Excellence
Semantic Mining in Biomedicine
(terminated)
Activities
organization of
workshop on UIMA for NLP
hold in conjunction with LREC 2008
member of the program committee of the
workshop on High-level Information Extraction
hold in conjunction with ECML/PKDD 2008
gave a tutorial on
UIMA for Semantic Text Mining in Biomedicine
toghether with Thilo Götz (IBM) and Ekaterina Buyko (JULIE Lab) at the SMBM 2008
co-chair of the
workshop on Active Learning for Natural Language Processing
hold in conjuction with HLT-NAACL 2009
co-chair of the
2nd German UIMA workshop
hold in conjunction with GSCL 2009
co-chair of the 2nd workshop on
Active Learning for Natural Language Processing
hold in conjuction with HLT-NAACL 2010
member of the program committee of the workshop
New Challenges for NLP Frameworks
hold in conjunction with LREC 2010
member of the program committee of the
CoNLL-2010 Shared Task (Learning to detect hedges and their scope in natural language text)
reviewing for the Semantics track of
COLING 2010
Awards
Best Paper Award at KCAP 2009
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