Folgen
Gerhard Paass
Gerhard Paass
Lead Scientist, Fraunhofer Institute for Intelligent Analysis and Information Systems
Bestätigte E-Mail-Adresse bei iais.fraunhofer.de
Titel
Zitiert von
Zitiert von
Jahr
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
16092005
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
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20