Publications Bernhard Pfahringer

Bernhard Pfahringer's publications:

If you need electronic copies, either use the Electronic Edition (EE) links supplied by the DBLP Bibliography Server, or email me for a pdf version.

2009

Jesse Read, Bernhard Pfahringer, Geoffrey Holmes, Eibe Frank: Classifier chains for multi-label classification,ECML/PKDD 2009, Bled, Slovenia.
Remco Bouckaert, Geoffrey Holmes, Bernhard Pfahringer, Dale Fletcher: Gaussian processes on graphics cards for NIRS, NIR2009, Bangkok, Thailand.
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer, Ricard Gavalda: Improving adaptive bagging methods for evolving data streams, ACML2009, Nanjing, China.
Bernhard Pfahringer, Dale Fletcher, Remco Bouckaert, Geoffrey Holmes: Random model trees: a competitive off-the-shelf technology for NIRS, NIR2009, Bangkok, Thailand.
Mark Hall, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, Ian H. Witten: The WEKA data mining software: an update, SIGKDD Explorations. v11, July. ACM, 2009. pp.10-18.
Stefan Mutter, Bernhard Pfahringer, Geoffrey Holmes: The positive effects of negative information: extending one-class classification models in binary proteomic sequence classification, AI2009, Melbourne, Australia.
Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer, Richard Kirkby, Ricard Gavalda: New Ensemble Methods for Evolving Data Streams. KDD2009, Paris, France.
Grant Anderson and Bernhard Pfahringer:Relational Random Forests based on Random Relational Rules, IJCAI2009, Pasadena, California, USA.

2008

Stefan Mutter, Bernhard Pfahringer, Geoffrey Holmes: Propositionalisation of Profile Hidden Markov Models for Biological Sequence Analysis. Australasian Conference on Artificial Intelligence 2008: 278-288
Xing Wu, Geoffrey Holmes, Bernhard Pfahringer: Mining Arbitrarily Large Datasets Using Heuristic k-Nearest Neighbour Search. Australasian Conference on Artificial Intelligence 2008: 355-361
Jesse Read, Bernhard Pfahringer, Geoffrey Holmes: Multi-label Classification Using Ensembles of Pruned Sets. ICDM 2008: 995-1000
Joaquin Vanschoren, Hendrik Blockeel, Bernhard Pfahringer, Geoffrey Holmes: Organizing the World's Machine Learning Information. ISoLA 2008: 693-708
Joaquin Vanschoren, Bernhard Pfahringer, Geoffrey Holmes: Learning from the Past with Experiment Databases. PRICAI 2008: 485-496
Bernhard Pfahringer, Geoffrey Holmes, Richard Kirkby: Handling Numeric Attributes in Hoeffding Trees. PAKDD2008, Osaka, Japan.
Grant Anderson and Bernhard Pfahringer:Exploiting Propositionalization based on Random Relational Rules for Semi-Supervised Learning,, PAKDD2008, Osaka, Japan.

2007

Bernhard Pfahringer, Claire Leschi, Peter Reutemann: Scaling Up Semi-supervised Learning: An Efficient and Effective LLGC Variant. PAKDD 2007: 236-247
Bernhard Pfahringer, Geoffrey Holmes, Richard Kirkby: New Options for Hoeffding Trees. Australian Conference on Artificial Intelligence 2007: 90-99
Grant Anderson and Bernhard Pfahringer:Clustering Relational Data based on Randomized Propositionalization, in Proceedings of the 17th International Conference on Inductive Logic Programming (ILP 2007), Corvallis, Oregon, USA, June 19-21, 2007.
Mutter, S. and Pfahringer, B.: A discriminative approach to structured biological data. Proc NZCSRSC'07, the Fifth New Zealand Computer Science Research Student Conference, Hamilton, New Zealand.

2006

Geoffrey Holmes, Bernhard Pfahringer, Richard Kirkby:Cache Hierarchy Inspired Compression: a Novel Architecture for Data Streams, Journal of Information Technology in Asia, 2006.
Grant Anderson and Bernhard Pfahringer:Random Relational Rules, in Proceedings of the 16th International Conference on Inductive Logic Programming (ILP 2006), Santiago de Compostela, Spain, August 24-27, 2006.
Eibe Frank and Bernhard Pfahringer:Improving on bagging with input smearing, in Proc 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Singapore. Springer, 2006.
Kurt Driessens, Peter Reutemann, Bernhard Pfahringer, and Claire Leschi:Using weighted nearest neighbor to benefit from unlabeled data, in Wee Keong Ng, Masaru Kitsuregawa, Jianzhong Li, and Kuiyu Chang, editors, Advances in Knowledge Discovery and Data Mining, 10th Pacific-Asia Conference, PAKDD 2006, volume 3918 of LNCS, pages 60-69, 2006.
Bernhard Pfahringer:A semi-supervised spam mail detector, Discovery Challenge Workshop, ECML/PKDD 2006.

2005

Stefan Kramer, Bernhard Pfahringer (Eds):Inductive Logic Programming, 15th International Conference, ILP2005, LNAI 3625
Stefan Kramer, Bernhard Pfahringer (Eds):Late-breaking papers, Inductive Logic Programming, 15th International Conference, ILP2005, TUM-I0510, Munich University of Technology
Bernhard Pfahringer, Peter Reutemann, Michael Mayo:A novel two stage scheme utilizing the test set for model selection in text classification. The 18th Autralian Joint Conference on Artificial Intelligence. Australia, University of Technology, Sydney, Sydney, Australia, 5-9 December, 2005.
Geoffrey Holmes, Richard Kirkby, Bernhard Pfahringer: Tie-Breaking in Hoeffding Trees, Second International Workshop on Knowledge Discovery from Data Streams, Porto, Portugal, 2005
Geoffrey Holmes, Richard Kirkby, Bernhard Pfahringer:Stress-testing Hoeffding Trees, 9th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD05) Porto, Portugal, 2005
Geoffrey Holmes, Bernhard Pfahringer, Richard Kirkby:Cache Hierarchy Inspired Compression: a Novel Architecture for Data Streams, Fourth International Conference on IT in Asia (CITA05), Kuching, Malaysia, 2005
Eibe Frank, Mark Hall, Geoffrey Holmes, Richard Kirkby, Bernhard Pfahringer, Ian H. Witten, and Len Trigg:WEKA: A Machine Learning Workbench for Data Mining. Data Mining and Knowledge Discovery Handbook. Springer-Verlag, 2005.

2004

Li M., Holmes G., Pfahringer B.:Clustering Large Datasets Using Cobweb and K-means in Tandem 17th Australian Joint Conference on Artificial Intelligence, Cairns, 2004
Reutemann P., Pfahringer B., Frank E.:A Toolbox for Learning from Relational Data with Propositional and Multi-Instance Learners, 17th Australian Joint Conference on Artificial Intelligence, Cairns, 2004
Kibriya A.M., Frank E., Pfahringer B., Holmes G.:Multinomial Naive Bayes for Text Categorization Revisited 17th Australian Joint Conference on Artificial Intelligence, Cairns, 2004
G. Holmes, R. Kirkby, B. Pfahringer.:Mining Data Streams using Option Trees. Workshop on Knowledge Discovery in Data Streams, 15th European Conference on Machine Learning (ECML), Pisa, 2004
Pfahringer B., Holmes G., Wang C.:Millions of Random Rules, Workshop on Advances in Inductive Rule Learning, 15th European Conference on Machine Learning (ECML), Pisa, 2004
Blockeel H., Dzeroski S., Kompare B., Kramer S., Pfahringer B., Van Laer W.:Experiments in Predicting Biodegradability, Journal of Applied Artificial Intelligence, 18/2, 2004.
Pfahringer B.:Sampling, ROC curves, and the Imbalanced Classes Problem, Working Paper, 2004
Holmes G., Kirkby R., Pfahringer B.:Batch-Incremental Learning for Mining Data Streams, Working Paper, 2004

2003

Frank E., Hall M., Pfahringer B.:Locally Weighted Naive Bayes, Nineteenth Conference on Uncertainty in Artificial Intelligence (UAI2003)
Weidmann N., Frank E., Pfahringer B.:A Two-Level Learning Method for Generalized Multi-instance problems, Fourteenth European Conference on Machine Learning (ECML2003)
Sauban M., Pfahringer B.:Text Classification using Document Profiling, Seventh European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD2003)
Pfahringer B., Holmes G.:Propositionalization through Stochastic Discrimination 13th International Conference on Inductive Logic Programming (ILP2003)
Holmes G., Pfahringer B., Kirkby R.:Mining Data Streams using Option Trees, Working paper 08/03, 2003

2002

Holmes G., Pfahringer B., Kirkby R., Frank E., Hall M.:Multiclass Alternating Decision Trees, ECML, 2002
Pfahringer B.:Data Mining Challenge Problems: any Lessons Learned? ICML Workshop DDLL, 2002
Clayton R., Cleary J.G., Pfahringer B., Utting M.:Optimizing Tabling Structures for Bottom-Up Logic Programming, International Workshop on Logic Based Program Development and Transformation (LOPSTR), 2002
Witten I.H., Frank E., Pfahringer B., Hall M.:Inside WEKA -- and Beyond the Book, Tutorial at ICML 2002
Pfahringer B.:Introduction to Data Mining, New Zealand Statistical Association, Data Mining Workshop 2002

2001

Clayton R., Cleary J., Pfahringer B., Utting M.:Intermediate Language for Tabling, working paper, 2001
Pfahringer B.:(The Futility of) Trying to Predict Carcinogenicity of Chemical Compounds, The Predictive Toxicology Challenge Workshop, Twelfth European Conference on Machine Learning (ECML2001), Freiburg, 2001
Pfahringer B., Holmes G, Schmidberger G.:Wrapping Boosters against Noise, Fourteenth Australian Joint Conference on Artificial Intelligence (AI'01), 2001
Pfahringer B., Holmes G, Kirkby R.:Optimizing the Induction of Alternating Decision Trees, in Cheung D., Williams G.J., Li Q. (eds.), Proceedings of the Fith Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (PAKDD2001), Springer, 2001
S. Kramer, G. Widmer, B. Pfahringer, M. De Groeve.:Prediction of Ordinal Classes Using Regression Trees, in Fundamenta Informaticae, special issue on ISMIS-2000, 2001
Gottmann E., Kramer S., Pfahringer B., Helma C.:Data Quality in Predictive Toxicology Part 2: Reproducibility of Rodent Carcinogenicity Experiments, Environmental Health Perspectives, 109(5):509-514, 2001.

2000

Pfahringer B., Bensusan H., Giraud-Carrier C.:Meta-Learning by Landmarking Various Learning Algorithms, in Langley P.(ed.), Proceedings of the 17th International Conference on Machine Learning (ICML-2000), Morgan Kaufmann, Los Altos/Palo Alto/San Francisco, 2000.
Fuernkranz J., Pfahringer B., Kaindl H., Kramer S.:Learning to Use Operational Advice, in Horn W.(ed.), ECAI 2000. Proceedings of the 14th European Conference on Artificial Intelligence, IOS, Amsterdam, pp.291-295, 2000
Kovar K., Fuernkranz J., Petrak J., Pfahringer B., Trappl R., Widmer G.:Searching for Patters in Political Events Sequences: Experiments with the KEDS Database, Cybernetics and Systems, 31(6), 649, 2000.
Kramer S., Widmer G., Pfahringer B., DeGroeve M.:Prediction of Ordinal Classes Using Regression Trees, Proceedings of the 12th International Symposium on Methodologies for Intelligent Systems (ISMIS'2000), Charlotte, N.C., 2000.
Pfahringer B.:Winning the KDD99 Classification Cup: Bagged Boosting, SIGKDD explorations, 1(2), 65-66, 2000.
Helma C., Kramer S., Pfahringer B., Gottmann E.:Data Quality in Predictive Toxicology Part 1: Identification of Chemical Structures and Calculation of Chemical Descriptors, Environmental Health Perspectives, 108:1029-1033, 2000.
Helma C, Gottmann E, Kramer S and Pfahringer B:The Application of Machine Learning Algorithms to Detect Chemical Properties Responsible for Carcinogenicity. in: Gundertofte K, Jorgensen FS (Eds.): Molecular Modeling and Prediction of Bioactivity, Kluwer Academic/Plenum Publishers, New York, pp 464-466, 2000.

1999

Giraud-Carrier C., Pfahringer B.(eds.):Proceedings of the ICML-99 Workshop on Recent Advances in Meta-Learning and Future Work Bled, Slovenia, 1999.
Pfahringer B., Kaindl H., Kramer S., Fürnkranz J.:Learning to Make Good Use of Operational Advice, in Proceedings of the ICML-99 Workshop on Machine Learning in Game Playing, Bled, Slovenia, 1999
Dzeroski S., Blockeel H., Kompare B., Kramer S., Pfahringer B., Van Laer W.:Experiments in Predicting Biodegradability, in Dzeroski S. and Flach P. (eds.): Inductive Logic Programming (ILP-99), Springer, Berlin/Heidelberg/New York/Tokyo, 1999.
Pfahringer, B., Gottmann, E., Kramer, S., Helma, C.,Representational/Efficiency Issues In Toxicological Knowledge Discovery, in Proceedings of the AAAI Spring Symposium 1999 on Predictive Toxicology, Stanford, March 1999.
Helma, C., Gottmann, E., Kramer, S., Pfahringer, B.,Data Quality Issues In Toxicological Knowledge Discovery, in Proceedings of the AAAI Spring Symposium 1999 on Predictive Toxicology, Stanford, March 1999.
Helma, C., Kramer, S., Pfahringer, B.: Carcinogenicity Prediction for Noncongeneric Compounds: Experiments with the Machine Learning Program SRT and Various Sets of Chemical Descriptors, in: Proceedings 12th European Symposium on Quantitative Structure-Activity Relationships, 1998.
Helma, C., Gottmann, E., Pfahringer, B., Kramer, S. Extraction of Structure-Activity Relationships for Biodegradability and Mutagenicity of Non-Congeneric Compounds Using Structural Regression Trees. Presentation at the American Chemical Society (ACS) Symposium on Data Mining Chemical Information Databases, 1999.
Helma, C., Gottmann, E., Kramer, S. and Pfahringer, B. Artificial Intelligence Methoden zur Vorhersage der Kanzerogenität organischer Verbindungen. in: Schöffl H, Spielmann H, Tritthart HA (Hrsg.): Ersatz- und Ergänzungsmethoden zu Tierversuchen, Springer Verlag, 1999.

1998

Fuernkranz J., Pfahringer B.:Guest Editorial: First-Order Knowledge Discovery in Databases, Applied Artificial Intelligence, 12(5), 345-362, 1998.
Helma C., Kramer S., Pfahringer B.:Carcinogenicity Prediction for Noncongeneric Compounds: Experiments with the Machine Learning Program SRT and Various Sets of Chemical Descriptors, Proc. of 12th European Symposium on Quantitative Structure-Activity Relationships, 1998.
Kramer S., Pfahringer B., Helma C.:Stochastic Propositionalization of Non-Determinate Background Knowledge, in Page D.(ed.): Inductive Logic Programming (ILP98), Springer, Berlin/Heidelberg/New York/Tokyo, 1998.
Pfahringer B.:Inducing Small and Accurate Decision Trees, TR-98-09, Oesterreichisches Forschungsinstitut fuer Artificial Intelligence, Wien, 1998.
Pfahringer B., Kramer S.:Discovering Compressive Partial Determinations in Mixed Numerical and Symbolic Domains, in Trappl R.(ed.), Cybernetics and Systems '98: Proc. of 14th European Meeting on Cybernetics and Systems Research, Austrian Society for Cybernetic Studies, Vienna, 2 vols., pp.884-889, 1998.
Widmer G., Kramer S., Pfahringer B., DeGroeve M.:Predicting Ordinal Classes in ILP, TR-98-08, Oesterreichisches Forschungsinstitut fuer Artificial Intelligence, Wien, 1998.

1997

Kramer S., Pfahringer B., Helma C.:Mining for Causes of Cancer: Machine Learning Experiments at Various Levels of Detail, Proc. of 3rd International Conference on Knowledge Discovery and Data Mining (KDD), AAAI Press, Menlo Park, 1997.
Pfahringer B.:Compression-Based Pruning of Decision Lists, in Someren M.van and Widmer G.(eds.), Machine Learning: ECML-97, Springer, Berlin/Heidelberg/New York/Tokyo, pp.199-212, 1997.
Pfahringer B.:On the Induction of Intelligible Ensembles, TR-97-30, Oesterreichisches Forschungsinstitut fuer Artificial Intelligence, Wien, 1997.
Pfahringer B., Witten I.H.:Improving Bagging Performance by Increasing Decision Tree Diversity, TR-97-31, Oesterreichisches Forschungsinstitut fuer Artificial Intelligence, Wien, 1997.

1996

Kramer S., Pfahringer B.:Efficient Search for Strong Partial Determinations, in Simoudis E. and Han J.(eds.), KDD-96: Proceedings Second International Conference on Knowledge Discovery & Data Mining, AAAI Press/MIT Press, Cambridge/Menlo Park, pp.371-374, 1996.
Pfahringer B.:A Multi-Agent Approach to Open Shop Scheduling: Adapting the Ant-Q Formalism, Oesterreichisches Forschungsinstitut fuer Artificial Intelligence, Wien, TR-96-09, 1996.
Pfahringer B.:OFAI Publishing Rules: A Case Study in Information Agents, Oesterreichisches Forschungsinstitut fuer Artificial Intelligence, Wien, TR-96-08, 1996.
Pfahringer B., Fuernkranz J.(eds.):Proceedings of the MLnet Familiarization Workshop on Data Mining with Inductive Logic Programming (ILP for KDD), Bari, Italy., 1996.

1995

Petta P., Pfahringer B.:Workshopreport: ``Designing Personalities for Synthetic Actors'', OeGAI Journal, 14(4), 1995.
Pfahringer B.:A New MDL Measure for Robust Rule Induction (Extended Abstract), in Lavrac N. and Wrobel S.(eds.), Machine Learning: ECML-95, Springer, Berlin/Heidelberg/New York/Tokyo, pp.331-334, 1995.
Pfahringer B.:Compression-Based Discretization of Continuous Attributes, in Prieditis A. and Russell S.(eds.), Proceedings of the 12th International Conference on Machine Learning (ICML'95), Morgan Kaufmann, Los Altos/Palo Alto/San Francisco, 1995.
Pfahringer B.:Compression-Based Feature Subset Selection, in Turney P.(ed.), IJCAI-95 Workshop on Data Engineering for Inductive Learning, IJCAI'95 Workshop Program Working Notes, Montreal, Canada, 1995.
Pfahringer B.:Evolving Good TSP Tours by Means of Heuristic Repair and Strong Crowding, Oesterreichisches Forschungsinstitut fuer Artificial Intelligence, Wien, TR-95-33, 1995.
Pfahringer B.:Practical Uses of the Minimum Description Length Principle in Inductive Learning, Doctoral thesis, Department for Medical Cybernetics and AI, University of Vienna, 1995.
Pfahringer B., Kramer S.:Compression-Based Evaluation of Partial Determinations, Proc. of 1st International Conference on Knowledge Discovery and Data Mining (KDD-95), Montreal, Canada, 1995.

1994

Pfahringer B.:CiPF 2.0: A Robust Constructive Induction System, Proc. of Workshop on Constructive Induction and Change of Representation, 11th International Conference on Machine Learning (ML-94/COLT-94), 1994.
Pfahringer B.:Controlling Constructive Induction in CiPF: An MDL Approach, in Bergadano F. and Raedt L.de(eds.), Machine Learning: ECML-94, Springer, Berlin/Heidelberg/New York/Tokyo, pp.242-256, 1994.
Pfahringer B.:Robust Constructive Induction, in Nebel B. and Dreschler-Fischer L.(eds.), KI-94: Advances in Artificial Intelligence, Springer, Berlin/Heidelberg/New York/Tokyo, pp.118-129, 1994.

1992

Mozetic I., Pfahringer B.:Improving Diagnostic Efficiency in KARDIO: Abstractions, Constraint Propagation, and Model Compilation, in Keravnou E.(ed.), Deep Models for Medical Knowledge Engineering, Elsevier, Amsterdam/New York, pp.1-25, 1992.
Pfahringer B.:CLP(gRel): Explicit Manipulation of (ground) Relational Dependencies in Logic Programming, TR-92-03, Oesterreichisches Forschungsinstitut fuer Artificial Intelligence, Wien, 1992.
Pfahringer B.:How to Integrate Specialized Solvers: A CLP Approach, TR-92-31, Oesterreichisches Forschungsinstitut fuer Artificial Intelligence, Wien, 1992.
Pfahringer B.:The Logical Way to Build a DL-based KR System, in MacGregor R., Issues in Description Logics: Users Meet Developers, AAAI Symposium Working Notes, 1992.
Pfahringer B.:Unifikationserweiterungen: Vergleich und moegliche Nutzung in der Wissensrepraesentation anhand ausgewaehlter Beispiele, TR-92-30, Oesterreichisches Forschungsinstitut fuer Artificial Intelligence, Wien, 1992.
Pfahringer B., Matiasek J.:A CLP Schema to Integrate Specialized Solvers and its Application to Natural Language Processing, TR-92-37, Oesterreichisches Forschungsinstitut fuer Artificial Intelligence, Wien, 1992.

1991

Buchberger E., Garner E., Heinz W., Matiasek J., Pfahringer B.:VIE-DU - A Second Generation Dialogue System, TR-91-04, Oesterreichisches Forschungsinstitut fuer Artificial Intelligence, Wien, 1991.
Buchberger E., Garner E., Heinz W., Matiasek J., Pfahringer B.:VIE-DU - Dialogue by Unification, in Kaindl H.(ed.), 7.Oesterreichische Artificial-Intelligence-Tagung, Springer, Berlin/Heidelberg/New York/Tokyo, pp.42-51, 1991.
Pfahringer B.:Theory Unification: Use and Support (Abstract), in Nebel B., et al., International Workshop on Terminological Logics, Dagstuhl-Seminar-Report, 12 (9119), 1991.

1990

Pfahringer B.: Constraintpropagation in Qualitative Modelling: Domain Variables Improve Diagnostic Efficiency Proc. AISB-91, pp. 129-135, Leeds, UK, April 16-19, 1991,Springer-Verlag.

1989

Pfahringer B.:Extending Explanation-Based Generalization, in Retti J. and Leidlmair K.(eds.), 5.Oesterreichische Artificial-Intelligence-Tagung, Springer, Berlin/Heidelberg/New York/Tokyo, pp.149-153, 1989.
Pfahringer B.:Integrating Definitions and Defaults, Oesterreichisches Forschungsinstitut fuer Artificial Intelligence, Wien, TR-89-8, 1989.
Trappl R., Porenta G., Pfahringer B.:Medical Expert Systems for Developing Countries: An Application in Primary Health Care, Microelectronics Monitor, 28,94-98, 1989.

1988

Porenta G., Binder T., Pfahringer B., Anvari A., Weber H.:Antiarrhythmic Strategies: A Knowledge Based System for Exploring Clinical Data, Pacing and Clinical Electrophysiology, 11(6)II (Proc.Cardiostim 88, Monaco), 1988.
Porenta G., Binder T., Pfahringer B., Anvari A., Weber H.:Evaluating Antiarrhythmic Strategies: A Knowledge-Based System for Exploring Clinical Data, Institut fuer Med.Kybernetik u. AI, Universitaet Wien, Bericht 88-04, 1988.
Porenta G., Pfahringer B., Hoberstorfer M., Trappl R.:A Decision Support System for Village Health Workers in Developing Countries, Applied Artificial Intelligence, 2(1)47-63, 1988.
Trost H., Pfahringer B.:VIE-KL: An Experiment in Hybrid Knowledge Representation, Oesterreichisches Forschungsinstitut fuer Artificial Intelligence, Wien, TR-88-8, 1988.

1987

Holzbaur C., Pfahringer B.:Synthesis of Hybrid Languages, Applied Artificial Intelligence, 1(1)39-52, 1987.
Horn W., Imhof H., Pfahringer B., Salomonowitz E.:A Radiological Expert System for the PC - Design and Implementation Issues, in Fox J., et al.(eds.), Proceedings of the European Conference on Artificial Intelligence in Medicine (AIME-87), Springer, Berlin/Heidelberg/New York/Tokyo, pp.169-176, 1987.
Imhof H., Horn W., Pfahringer B.:Computerunterstuetzte radiologische Nierendiagnostik - Anwendung eines Expertensystems, Proc. of 5.Grazer radiologisches Symposium, Springer, Berlin, 1987.
Porenta G., Pfahringer B., Binder T., Rimpfl T., Norman G., Weber H.:A Decision Support System for Selecting and Assessing Antiarrhythmic Therapies, Proc. of Computers in Cardiology 1987, IEEE, Washington, DC, 1987.
Porenta G., Pfahringer B., Hoberstorfer M., Trappl R.:A Decision Support System for Village Health Workers, in Buchberger E., et al.(eds.), Artificial Intelligence - Perspectives and Implications, CompLex, Norwegian University Press, Oslo, 11/87, 1987.

1986

Hoberstorfer M., Horn W., Pfahringer B., Porenta G., Trappl R., Widmer G.:Medizinische Expertensysteme am PC: Zwei Implementierungen fuer Industrie- und Entwicklungslaender, Berichte der Oesterreichischen Studiengesellschaft fuer Kybernetik, Wien, 1986.
Hoberstorfer M., Pfahringer B., Porenta G., Trappl R.:Ein medizinisches Expertensystem am PC: Entscheidungsunterstuetzung fuer einen Village Health Worker in Entwicklungslaendern, in Rappelsberger P., et al.(eds.), Medizinische Informatik '86, Oldenbourg, Muenchen/Wien, pp.347-350, 1986.
Horn W., Pfahringer B., Imhof H., Salomonowitz E.:Ein entscheidungsunterstuetzendes Expertensystem fuer die Radiodiagnostik, in Rappelsberger P., et al.(eds.), Medizinische Informatik '86, Oldenbourg, Muenchen/Wien, 1986.
Pfahringer B., Holzbaur C.:Mixing Prolog and Lisp, in Trappl R.(ed.), Cybernetics and Systems '86, Reidel, Dordrecht/Boston, pp.759-765, 1986.

1985

Pfahringer B.:VIEnna Knowledge Engineering Tool - Der Frame Teil, Diploma thesis, Department for Medical Cybernetics and AI, University of Vienna, 1985.
Pfahringer B., Holzbaur C.:VIE-KET: Frames + Prolog, in Trost H. and Retti J.(eds.), Oesterreichische Artificial Intelligence-Tagung, Springer, Berlin/Heidelberg/New York/Tokyo, pp.132-139, 1985.