Martin Atzmüller - researchr alias

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2023

Computational approaches to Explainable Artificial Intelligence: Advances in theory, applications and trendsJ. M. Górriz, I. Álvarez Illán, Agustín Álvarez Marquina, Juan Eloy Arco, Martin Atzmüller, F. Ballarini, Emilia I. Barakova, Guido Bologna, María Paula Bonomini, Germán Castellanos-Domínguez, Diego Castillo-Barnes, S. B. Cho, A. Ricardo Contreras, J. M. Cuadra, Enrique Domínguez, Francisco Domínguez-Mateos, Richard J. Duro, David A. Elizondo, Antonio Fernández-Caballero 0001, Eduardo Fernández 0001, Marco A. Formoso, Nicolás Gallego-Molina, Javier Gamazo, Javier González Jiménez, Jacob Rodriguez-Rivero, Carlos Garre del Olmo, F. Javier Garrigós, Andrés Gómez-Rodellar, Pedro Gómez Vilda, Manuel Graña, Bernabé Rodríguez-Tapia, Sophie C. F. Hendrikse, Carmen Jimenez-Mesa, Marina Jodra-Chuan, Vicente Julián, G. Gabriela Kotz, Krzysztof Kutt, Matthew Leming, Javier de Lope Asiaín, Beatriz del Cisne Macas Ordónez, V. Marrero-Aguiar, J. J. Martinez, Francisco Jesús Martínez-Murcia, Rafael Martínez-Tomás, Jirí Mekyska, Grzegorz J. Nalepa, Paulo Novais, D. Orellana, Andrés Ortiz, Daniel Palacios-Alonso, José T. Palma, A. Pereira, Pedro Pinacho Davidson, M. A. Pinninghoff, M. Ponticorvo, Alexandra Psarrou, Javier Ramírez 0001, Mariano Rincón, V. Rodellar-Biarge, Ignacio Rodríguez-Rodríguez, Peter H. M. P. Roelofsma, J. Santos, Diego Salas-Gonzalez, Pedro Salcedo Lagos, Fermín Segovia, Afshin Shoeibi, M. Silva, Dragan Simic, John Suckling, Jan Treur, Athanasios Tsanas, R. Varela, S. H. Wang, W. Wang, Y. D. Zhang, H. Zhu, Z. Zhu, J. M. Ferrández-Vicente. inffus, 100:101945, December 2023. [doi]

2021

A Hybrid Information Extraction Approach using Transfer Learning on Richly-Structured DocumentsArnab Ghosh Chowdhury, Nils Schut, Martin Atzmüller. lwa 2021: 13-25 [doi]

2019

Graph Summarization for Computational Sensemaking on Complex Industrial Event LogsStefan Bloemheuvel, Benjamin Klöpper, Martin Atzmüller. BPM 2019: 417-429 [doi]

2018

Towards Estimating Collective Motor Behavior: Aware of Self vs. Aware of the OtherLisa E. Rombout, Martin Atzmüller, Marie Postma-Nilsenová. afcai 2018: [doi]

2016

Advances in Exploratory Pattern Analytics on Ubiquitous Data and Social MediaMartin Atzmüller. BIRTHDAY 2016: 184-207 [doi]

2014

2012

A Personality Based Design Approach Using Subgroup DiscoveryKay Behrenbruch, Martin Atzmüller, Christoph Evers, Ludger Schmidt, Gerd Stumme, Kurt Geihs. HCSE 2012: 259-266 [doi]

2011

Enhancing Social Interactions at ConferencesMartin Atzmüller, Dominik Benz, Stephan Doerfel, Andreas Hotho, Robert Jäschke, Bjoern Elmar Macek, Folke Mitzlaff, Christoph Scholz, Gerd Stumme. it, 53(3):101-107, 2011. [doi]

2010

Fast Discovery of Relevant Subgroup PatternsFlorian Lemmerich, Mathias Rohlfs, Martin Atzmüller. flairs 2010: [doi]

EWMA control charts for monitoring binary processes with applications to medical diagnosis dataChristian H. Weiß, Martin Atzmüller. qre, 26(8):795-805, 2010. [doi]

2009

A Semi-Automatic Approach for Confounding-Aware Subgroup DiscoveryMartin Atzmüller, Frank Puppe, Hans-Peter Buscher. ijait, 18(1):81-98, 2009. [doi]

2008

A case-based approach for characterization and analysis of subgroup patternsMartin Atzmüller, Frank Puppe. apin, 28(3):210-221, 2008. [doi]

Rule-Based Information Extraction for Structured Data Acquisition using TextMarkerMartin Atzmüller, Peter Klügl, Frank Puppe. lwa 2008: 1-7

Semi-Automatic Refinement and Assessment of Subgroup PatternsMartin Atzmüller, Frank Puppe. flairs 2008: 323-328

A Methodological Approach for the Effective Modeling of Bayesian NetworksMartin Atzmüller, Florian Lemmerich. ki 2008: 160-168 [doi]

Integrating the Rule-Based IE Component TextMarker into UIMAPeter Klügl, Martin Atzmüller, Frank Puppe. lwa 2008: 73-77

Test-Driven Development of Complex Information Extraction Systems using TextMarkerPeter Klügl, Martin Atzmüller, Frank Puppe. ki 2008: [doi]

Generating Evaluation Data using Bayesian Networks - A Simple and Effective Modeling MethodologyFlorian Lemmerich, Martin Atzmüller. lwa 2008: 69-76

Application and Evaluation of a Medical Knowledge System in Sonography (SONOCONSULT)Frank Puppe, Martin Atzmüller, Georg Buscher, Matthias Hüttig, Hardi Luehrs, Hans-Peter Buscher. ecai 2008: 683-687 [doi]

2007

Experience Management with Task-Configurations and Task-Patterns for Descriptive Data MiningMartin Atzmüller. ki 2007: [doi]

Knowledge-Intensive Subgroup MiningMartin Atzmüller. ki, 21(2):53-54, 2007. [doi]

Pattern-Constrained Test Case GenerationMartin Atzmüller, Joachim Baumeister, Frank Puppe. flairs 2007: 518-523

Rapid knowledge capture using subgroup discovery with incremental refinementMartin Atzmüller, Peter Klügl, Joachim Baumeister, Frank Puppe. kcap 2007: 31-38 [doi]

Towards Confounding-Aware Subgroup DiscoveryMartin Atzmüller, Frank Puppe. lwa 2007: 87-93

Causal Subgroup Analysis for Detecting ConfoundingMartin Atzmüller, Frank Puppe. wlp 2009: 136-148 [doi]

Using Declarative Specifications of Domain Knowledge for Descriptive Data MiningMartin Atzmüller, Dietmar Seipel. wlp 2009: 149-164 [doi]

Onto Confounding-Aware Subgroup DiscoveryMartin Atzmüller, Frank Puppe, Hans-Peter Buscher. ictai 2007: 163-170 [doi]

2006

Knowledge-intensive subgroup mining: techniques for automatic and interactive discoveryMartin Atzmüller. PhD thesis, Julius Maximilian University of Würzburg, 2006. [doi]

Case-Based Characterization and Analysis of Subgroup PatternsMartin Atzmüller. lwa 2006: 237-244 [doi]

A Datagenerator for Evaluating Machine Learning MethodsMartin Atzmüller, Joachim Baumeister, Mario Goller, Frank Puppe. ki, 20(3):57-63, 2006. [doi]

Semi-automatic learning of simple diagnostic scores utilizing complexity measuresMartin Atzmüller, Joachim Baumeister, Frank Puppe. artmed, 37(1):19-30, 2006. [doi]

A Methodological View on Knowledge-Intensive Subgroup DiscoveryMartin Atzmüller, Frank Puppe. ekaw 2006: 318-325 [doi]

Introspective Subgroup Analysis for Interactive Knowledge RefinementMartin Atzmüller, Joachim Baumeister, Frank Puppe. flairs 2006: 402-407

SD-Map - A Fast Algorithm for Exhaustive Subgroup DiscoveryMartin Atzmüller, Frank Puppe. pkdd 2006: 6-17 [doi]

Conservative and Creative Strategies for the Refinement of Scoring RulesJoachim Baumeister, Martin Atzmüller, Peter Klügl, Frank Puppe. flairs 2006: 408-413

2005

Semi-Automatic Visual Subgroup Mining using VIKAMINEMartin Atzmüller, Frank Puppe. jucs, 11(11):1752-1765, 2005. [doi]

Subgroup Mining for Interactive Knowledge RefinementMartin Atzmüller, Joachim Baumeister, Achim Hemsing, Ernst-Jürgen Richter, Frank Puppe. aime 2005: 453-462 [doi]

Exploiting Background Knowledge for Knowledge-Intensive Subgroup DiscoveryMartin Atzmüller, Frank Puppe, Hans-Peter Buscher. IJCAI 2005: 647-652 [doi]

Exemplifying Subgroup Mining Results for Interactive Knowledge RefinementMartin Atzmüller, Joachim Baumeister, Frank Puppe. lit 2005: 101-106

Clinical Experiences with a Knowledge-Based System in Sonography (SonoConsult)Frank Puppe, Georg Buscher, Martin Atzmüller, Matthias Hüttig, Hans-Peter Buscher. wm 2005: 299-304

Clinical Experiences with a Knowledge-Based System in Sonography (SonoConsult)Frank Puppe, Georg Buscher, Martin Atzmüller, Matthias Hüttig, Hans-Peter Buscher. wm 2005: 319-329 [doi]

2004

2003

Inductive Learning of Simple Diagnostic ScoresMartin Atzmüller, Joachim Baumeister, Frank Puppe. ismda 2003: 23-30 [doi]

Evaluation of two Strategies for Case-Based Diagnosis handling Multiple FaultsMartin Atzmüller, Joachim Baumeister, Frank Puppe. wm 2003: 275-276

2002

Inductive Learning for Case-Based Diagnosis with Multiple FaultsJoachim Baumeister, Martin Atzmüller, Frank Puppe. ewcbr 2002: 28-42 [doi]

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