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Christian Poelitz
Christian Poelitz
Microsoft Research
tu-dortmund.de의 이메일 확인됨 - 홈페이지
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What is it like to program with artificial intelligence?
A Sarkar, AD Gordon, C Negreanu, C Poelitz, SS Ragavan, B Zorn
arXiv preprint arXiv:2208.06213, 2022
1182022
Discovering bits of place histories from people's activity traces
G Andrienko, N Andrienko, M Mladenov, M Mock, C Pölitz
2010 IEEE symposium on visual analytics science and technology, 59-66, 2010
552010
A framework for using self-organising maps to analyse spatio-temporal patterns, exemplified by analysis of mobile phone usage
G Andrienko, N Andrienko, P Bak, S Bremm, D Keim, T von Landesberger, ...
Journal of Location based services 4 (3-4), 200-221, 2010
542010
Identifying place histories from activity traces with an eye to parameter impact
G Andrienko, N Andrienko, M Mladenov, M Mock, C Politz
IEEE Transactions on Visualization and Computer Graphics 18 (5), 675-688, 2011
472011
Extracting events from spatial time series
G Andrienko, N Andrienko, M Mladenov, M Mock, C Poelitz
2010 14th International Conference Information Visualisation, 48-53, 2010
332010
Improving session recommendation with recurrent neural networks by exploiting dwell time
A Dallmann, A Grimm, C Pölitz, D Zoller, A Hotho
arXiv preprint arXiv:1706.10231, 2017
192017
Adaptive burst detection in a stream engine
M Karnstedt, D Klan, C Pölitz, KU Sattler, C Franke
Proceedings of the 2009 ACM symposium on Applied Computing, 1511-1515, 2009
192009
Finding arbitrary shaped clusters with related extents in space and time
C Pölitz, G Andrienko, N Andrienko
152010
Combining a rule-based approach and machine learning in a good-example extraction task for the purpose of lexicographic work on contemporary standard German
L Lemnitzer, C Pölitz, J Didakowski, A Geyken
Proceedings of the eLex 2015 conference, 11-13, 2015
142015
Towards Burst Detection for Non-Stationary Stream Data.
D Klan, M Karnstedt, C Pölitz, KU Sattler
LWA, 57-60, 2008
142008
Interpretable domain adaptation via optimization over the Stiefel manifold
C Pölitz, W Duivesteijn, K Morik
Machine Learning 104, 315-336, 2016
122016
Learning semantic relatedness from human feedback using metric learning
T Niebler, M Becker, C Pölitz, A Hotho
arXiv preprint arXiv:1705.07425, 2017
92017
Using data mining and the clarin infrastructure to extend corpus-based linguistic research
T Bartz, C Pölitz, K Morik, A Storrer
92015
MAGIC: Generating Self-Correction Guideline for In-Context Text-to-SQL
A Askari, C Poelitz, X Tang
arXiv preprint arXiv:2406.12692, 2024
72024
Using a Maximum Entropy Classifier to link “good” corpus examples to dictionary senses
A Geyken, C Pölitz, T Bartz
Electronic lexicography in the 21st century: linking lexical data in the …, 2015
72015
Investigation of word senses over time using linguistic corpora
C Pölitz, T Bartz, K Morik, A Störrer
Text, Speech, and Dialogue: 18th International Conference, TSD 2015, Pilsen …, 2015
72015
InstructExcel: A Benchmark for Natural Language Instruction in Excel
J Payan, S Mishra, M Singh, C Negreanu, C Poelitz, C Baral, S Roy, ...
arXiv preprint arXiv:2310.14495, 2023
52023
What is it like to program with artificial intelligence?(2022)
A Sarkar, AD Gordon, C Negreanu, C Pölitz, SS Ragavan, B Zorn
arXiv preprint cs.HC/2208.06213 33, 2022
52022
Neue Möglichkeiten der Arbeit mit strukturierten Sprachressourcen in den Digital Humanities mithilfe von Data-Mining
T Bartz, M Beißwenger, C Pölitz, N Radtke, A Storrer
Lecture Notes in Computer Science, Posters, 2014
52014
What is it like to program with artificial intelligence? arXiv 2022
A Sarkar, AD Gordon, C Negreanu, C Poelitz, SS Ragavan, B Zorn
arXiv preprint arXiv:2208.06213, 0
5
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