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Gerhard Paass
Gerhard Paass
Lead Scientist, Fraunhofer Institute for Intelligent Analysis and Information Systems
Verified email at iais.fraunhofer.de
Title
Cited by
Cited by
Year
From recombination of genes to the estimation of distributions I. Binary parameters
H Mühlenbein, G Paass
International conference on parallel problem solving from nature, 178-187, 1996
16571996
A brief survey of text mining
A Hotho, A Nürnberger, G Paaß
LDV Forum-GLDV Journal for Computational Linguistics and Language Technology …, 2005
16082005
Authorship attribution with support vector machines
J Diederich, J Kindermann, E Leopold, G Paass
Applied intelligence 19, 109-123, 2003
5412003
Improved Phishing Detection using Model-Based Features.
A Bergholz, JH Chang, G Paass, F Reichartz, S Strobel
CEAS, 2008
2232008
New filtering approaches for phishing email
A Bergholz, J De Beer, S Glahn, MF Moens, G Paaß, S Strobel
Journal of computer security 18 (1), 7-35, 2010
2152010
Disclosure risk and disclosure avoidance for microdata
G Paass
Journal of Business & Economic Statistics 6 (4), 487-500, 1988
1821988
Statistical match: evaluation of existing procedures and improvements by using additional information
G Paass
Microanalytic Simulation Models to Support Social and Financial Policy, 401-420, 1986
761986
Assessing and improving neural network predictions by the bootstrap algorithm
G Paass
Advances in Neural Information Processing Systems 5, 1992
691992
Probabilistic logic
G Paass
Non-Standard Logics for Automated Reasoning, 1988
631988
From names to entities using thematic context distance
A Pilz, G Paaß
Proceedings of the 20th ACM international conference on Information and …, 2011
602011
Data mining and text mining for science & technology research
E Leopold, M May, G Paaß
Handbook of quantitative science and technology research: the use of …, 2004
572004
Datenzugang, Datenschutz und Anonymisierung
G Paaß, U Wauschkuhn
Oldenbourg Wissenschaftsverlag, 1985
571985
Künstliche Intelligenz: Was steckt hinter der Technologie der Zukunft?
G Paaß, D Hecker
Springer Fachmedien Wiesbaden GmbH, 2020
552020
SVM classification using sequences of phonemes and syllables
G Paaß, E Leopold, M Larson, J Kindermann, S Eickeler
European Conference on Principles of Data Mining and Knowledge Discovery …, 2002
492002
Dependency tree kernels for relation extraction from natural language text
F Reichartz, H Korte, G Paass
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2009
462009
Machine learning for document structure recognition
G Paaß, I Konya
Modeling, Learning, and Processing of Text Technological Data Structures …, 2012
442012
Semantic relation extraction with kernels over typed dependency trees
F Reichartz, H Korte, G Paass
Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010
432010
Bayesian query construction for neural network models
G Paass, J Kindermann
Advances in Neural Information Processing Systems 7, 1994
411994
A logic-based approach to relation extraction from texts
T Horváth, G Paass, F Reichartz, S Wrobel
Inductive Logic Programming: 19th International Conference, ILP 2009, Leuven …, 2010
262010
Error correcting codes with optimized Kullback-Leibler distances for text categorization
J Kindermann, G Paaß, E Leopold
European Conference on Principles of Data Mining and Knowledge Discovery …, 2001
252001
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