Article (kluegl2013exploiting)
Kluegl, P.; Toepfer, M.; Lemmerich, F.; Hotho, A. & Puppe, F.
Exploiting Structural Consistencies with Stacked Conditional Random Fields
Mathematical Methodologies in Pattern Recognition and Machine Learning Springer Proceedings in Mathematics & Statistics,
2013, 30, 111-125
Incollection (ABP:11)
Atzmueller, M.; Beer, S. & Puppe, F.
Brüggemann, S. & d’Amato, C. (ed.)
Data Mining, Validation and Collaborative Knowledge Capture
IGI Global,
2012, 149-167
Inproceedings (conf/pkdd/KluglTLHP12)
Klügl, P.; Toepfer, M.; Lemmerich, F.; Hotho, A. & Puppe, F.
Flach, P. A.; Bie, T. D. & Cristianini, N. (ed.)
Collective Information Extraction with Context-Specific Consistencies.
Springer,
2012, 7523, 728-743
Inproceedings (kluegl2012stacked)
Klügl, P.; Toepfer, M.; Lemmerich, F.; Hotho, A. & Puppe, F.
Carmona, P. L.; Sánchez, J. S. & Fred, A. (ed.)
Stacked Conditional Random Fields Exploiting Structural Consistencies
SciTePress,
2012, 240-248
Incollection (ABP:11)
Atzmueller, M.; Beer, S. & Puppe, F.
Brüggemann, S. & d’Amato, C. (ed.)
Data Mining, Validation and Collaborative Knowledge Capture
IGI Global,
2011
Inproceedings (toepfer2011segmentation)
Toepfer, M.; Kluegl, P.; Hotho, A. & Puppe, F.
Segmentation of References with Skip-Chain Conditional Random Fields for Consistent Label Transitions
2011
Inproceedings (2010-KI-KHP)
Kluegl, P.; Hotho, A. & Puppe, F.
Dillmann, R.; Beyerer, J.; Hanebeck, U. D. & Schultz, T. (ed.)
Local Adaptive Extraction of References
Springer,
2010, 40-47
Inproceedings (kdml21)
Toepfer, M.; Kluegl, P.; Hotho, A. & Puppe., F.
Atzmüller, M.; Benz, D.; Hotho, A. & Stumme, G. (ed.)
Conditional Random Fields For Local Adaptive Reference Extraction
2010
Inproceedings (ABP:09)
Atzmueller, M.; Beer, S. & Puppe, F.
A Data Warehouse-Based Approach for Quality Management, Evaluation and Analysis of Intelligent Systems using Subgroup Mining
AAAI Press,
2009, 372-377
Article (APB:09)
Atzmueller, M.; Puppe, F. & Buscher, H.-P.
A Semi-Automatic Approach for Confounding-Aware Subgroup Discovery
International Journal on Artificial Intelligence Tools (IJAIT),
2009, 18, 1 - 18
Inproceedings (ABHMLP:08)
Atzmueller, M.; Beer, S.; Hörnlein, A.; Melcher, R.; Lührs, H. & Puppe, F.
Design and Implementation of a Data Warehouse for Quality Management, System Evaluation and Knowledge Discovery in the Medical Domain
2008
Inproceedings (PABHLB:08)
Puppe, F.; Atzmueller, M.; Buscher, G.; Huettig, M.; Lührs, H. & Buscher, H.-P.
Application and Evaluation of a Medical Knowledge-System in Sonography (SonoConsult)
2008
Inproceedings (AP:07a)
Atzmueller, M. & Puppe, F.
Causal Subgroup Analysis for Detecting Confounding
2007
Inproceedings (ABKP:07)
Atzmueller, M.; Baumeister, J.; Klügl, P. & Puppe, F.
Rapid Knowledge Capture Using Subgroup Discovery with Incremental Refinement
ACM Press,
2007, 31-38
Inproceedings (AP:06a)
Atzmueller, M. & Puppe, F.
Case-Based Characterization and Analysis of Subgroup Patterns
University of Hildesheim,
2006
Inproceedings (AP:06a)
Atzmueller, M. & Puppe, F.
SD-Map -- A Fast Algorithm for Exhaustive Subgroup Discovery
2006, 6-17
Inproceedings (BAKP:06)
Baumeister, J.; Atzmueller, M.; Kluegl, P. & Puppe, F.
Sutcliffe, G. & Goebel, R. (ed.)
Conservative and Creative Strategies for the Refinement of Scoring Rules
AAAI Press,
2006, 408-413
Inproceedings (ABP:05)
Atzmueller, M.; Baumeister, J. & Puppe, F.
Exemplifying Subgroup Mining Results for Interactive Knowledge Refinement
2005, 101-106
Inproceedings (ABHRP:05)
Atzmueller, M.; Baumeister, J.; Hemsing, A.; Richter, E.-J. & Puppe, F.
Subgroup Mining for Interactive Knowledge Refinement
2005, 453-462
Inproceedings (BAP:02)
Baumeister, J.; Atzmueller, M. & Puppe, F.
Inductive Learning for Case-Based Diagnosis with Multiple Faults
2002, 2416, 28-42