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Nada Lavrac
2010 – today
- 2013
[j51]Laura Langohr, Vid Podpecan, Marko Petek, Igor Mozetic, Kristina Gruden, Nada Lavrac, Hannu Toivonen: Contrasting Subgroup Discovery. Comput. J. 56(3): 289-303 (2013)- [j50]Anze Vavpetic, Nada Lavrac: Semantic Subgroup Discovery Systems and Workflows in the SDM-Toolkit. Comput. J. 56(3): 304-320 (2013)
- [j49]Miha Grcar, Nejc Trdin, Nada Lavrac: A Methodology for Mining Document-Enriched Heterogeneous Information Networks. Comput. J. 56(3): 321-335 (2013)
- [c80]Matic Perovsek, Anze Vavpetic, Bojan Cestnik, Nada Lavrac: A Wordification Approach to Relational Data Mining. Discovery Science 2013: 141-154
- [c79]Anze Vavpetic, Petra Kralj Novak, Miha Grcar, Igor Mozetic, Nada Lavrac: Semantic Data Mining of Financial News Articles. Discovery Science 2013: 294-307
- [c78]Dragana Miljkovic, Vid Podpecan, Tjasa Stare, Igor Mozetic, Kristina Gruden, Nada Lavrac: Incremental revision of biological networks from texts. IWBBIO 2013: 1-9
- [c77]Borut Sluban, Nada Lavrac: ViperCharts: Visual Performance Evaluation Platform. ECML/PKDD (3) 2013: 650-653
- [c76]Jasmina Smailovic, Miha Grcar, Nada Lavrac, Martin Znidarsic: Predictive Sentiment Analysis of Tweets: A Stock Market Application. CHI-KDD 2013: 77-88
- [c75]Matjaz Jursic, Bojan Cestnik, Tanja Urbancic, Nada Lavrac: HCI Empowered Literature Mining for Cross-Domain Knowledge Discovery. CHI-KDD 2013: 124-135
- 2012
- [b3]Johannes Fürnkranz, Dragan Gamberger, Nada Lavrac: Foundations of Rule Learning. Cognitive Technologies, Springer 2012, ISBN 978-3-540-75196-0, pp. 1-298
- [j48]Ingrid Petric, Bojan Cestnik, Nada Lavrac, Tanja Urbancic: Outlier Detection in Cross-Context Link Discovery for Creative Literature Mining. Comput. J. 55(1): 47-61 (2012)
- [j47]Vid Podpecan, Monika Zemenova, Nada Lavrac: Orange4WS Environment for Service-Oriented Data Mining. Comput. J. 55(1): 82-98 (2012)
- [c74]Dragana Miljkovic, Matjaz Depolli, Igor Mozetic, Nada Lavrac, Tjasa Stare, Marko Petek, Kristina Gruden: Constraint-driven optimization of plant defense model parameters. BIBM Workshops 2012: 570-574
- [c73]Matic Perovsek, Anze Vavpetic, Nada Lavrac: A Wordification Approach to Relational Data Mining: Early Results. ILP (Late Breaking Papers) 2012: 56-61
- [c72]Borut Sluban, Senja Pollak, Roel Coesemans, Nada Lavrac: Irregularity Detection in Categorized Document Corpora. LREC 2012: 1598-1603
- [c71]Janez Kranjc, Vid Podpecan, Nada Lavrac: ClowdFlows: A Cloud Based Scientific Workflow Platform. ECML/PKDD (2) 2012: 816-819
- [c70]Anze Vavpetic, Vid Podpecan, Stijn Meganck, Nada Lavrac: Explaining Subgroups through Ontologies. PRICAI 2012: 625-636
- [p10]Matjaz Jursic, Borut Sluban, Bojan Cestnik, Miha Grcar, Nada Lavrac: Bridging Concept Identification for Constructing Information Networks from Text Documents. Bisociative Knowledge Discovery 2012: 66-90
- [p9]Ingrid Petric, Bojan Cestnik, Nada Lavrac, Tanja Urbancic: Bisociative Knowledge Discovery by Literature Outlier Detection. Bisociative Knowledge Discovery 2012: 313-324
- [p8]Borut Sluban, Matjaz Jursic, Bojan Cestnik, Nada Lavrac: Exploring the Power of Outliers for Cross-Domain Literature Mining. Bisociative Knowledge Discovery 2012: 325-337
- [p7]Matjaz Jursic, Bojan Cestnik, Tanja Urbancic, Nada Lavrac: Bisociative Literature Mining by Ensemble Heuristics. Bisociative Knowledge Discovery 2012: 338-358
- [p6]Igor Mozetic, Nada Lavrac: Applications and Evaluation: Overview. Bisociative Knowledge Discovery 2012: 359-363
- [p5]Igor Mozetic, Nada Lavrac, Vid Podpecan, Petra Kralj Novak, Helena Motaln, Marko Petek, Kristina Gruden, Hannu Toivonen, Kimmo Kulovesi: Semantic Subgroup Discovery and Cross-Context Linking for Microarray Data Analysis. Bisociative Knowledge Discovery 2012: 379-389
- [p4]Dragana Miljkovic, Vid Podpecan, Miha Grcar, Kristina Gruden, Tjasa Stare, Marko Petek, Igor Mozetic, Nada Lavrac: Modelling a Biological System: Network Creation by Triplet Extraction from Biological Literature. Bisociative Knowledge Discovery 2012: 427-437
- 2011
- [j46]Vid Podpecan, Nada Lavrac, Igor Mozetic, Petra Kralj Novak, Igor Trajkovski, Laura Langohr, Kimmo Kulovesi, Hannu Toivonen, Marko Petek, Helena Motaln, Kristina Gruden: SegMine workflows for semantic microarray data analysis in Orange4WS. BMC Bioinformatics 12: 416 (2011)
- [j45]Monika Záková, Petr Kremen, Filip Zelezný, Nada Lavrac: Automating Knowledge Discovery Workflow Composition Through Ontology-Based Planning. IEEE T. Automation Science and Engineering 8(2): 253-264 (2011)
- [c69]Borut Sluban, Matjaz Jursic, Bojan Cestnik, Nada Lavrac: Evaluating Outliers for Cross-Context Link Discovery. AIME 2011: 343-347
- [c68]Miha Grcar, Nada Lavrac: A Methodology for Mining Document-Enriched Heterogeneous Information Networks. Discovery Science 2011: 107-121
- [c67]Nada Lavrac, Anze Vavpetic, Larisa N. Soldatova, Igor Trajkovski, Petra Kralj Novak: Using Ontologies in Semantic Data Mining with SEGS and g-SEGS. Discovery Science 2011: 165-178
- [e8]Mor Peleg, Nada Lavrac, Carlo Combi (Eds.): Artificial Intelligence in Medicine - 13th Conference on Artificial Intelligence in Medicine, AIME 2011, Bled, Slovenia, July 2-6, 2011. Proceedings. Lecture Notes in Computer Science 6747, Springer 2011, ISBN 978-3-642-22217-7
- [i1]Dragan Gamberger, Nada Lavrac: Expert-Guided Subgroup Discovery: Methodology and Application. CoRR abs/1106.4576 (2011)
- 2010
- [j44]Borut Sluban, Nada Lavrac: Supporting the search for cross-context links by outlier detection methods. BMC Bioinformatics 11(S-5): P2 (2010)
- [j43]Matjaz Jursic, Igor Mozetic, Miha Grcar, Bojan Cestnik, Nada Lavrac: Identification of concepts bridging diverse biomedical domains. BMC Bioinformatics 11(S-5): P4 (2010)
- [j42]Matjaz Jursic, Igor Mozetic, Tomaz Erjavec, Nada Lavrac: LemmaGen: Multilingual Lemmatisation with Induced Ripple-Down Rules. J. UCS 16(9): 1190-1214 (2010)
- [c66]Miha Grcar, Vid Podpecan, Matjaz Jursic, Nada Lavrac: Efficient Visualization of Document Streams. Discovery Science 2010: 174-188
- [c65]Borut Sluban, Dragan Gamberger, Nada Lavrac: Advances in Class Noise Detection. ECAI 2010: 1105-1106
- [c64]Vid Podpecan, Monika Záková, Nada Lavrac: Workflow Construction for Service-Oriented Knowledge Discovery. ISoLA (1) 2010: 313-327
- [c63]Vid Podpecan, Miha Grcar, Nada Lavrac: Semi-supervised Constrained Clustering: An Expert-Guided Data Analysis Methodology. PRICAI 2010: 219-230
- [c62]Borut Sluban, Dragan Gamberger, Nada Lavrac: Performance Analysis of Class Noise Detection Algorithms. STAIRS 2010: 303-314
- [p3]Nada Lavrac, Blaz Zupan: Data Mining in Medicine. Data Mining and Knowledge Discovery Handbook 2010: 1111-1136
- [p2]Nada Lavrac, Johannes Fürnkranz, Dragan Gamberger: Explicit Feature Construction and Manipulation for Covering Rule Learning Algorithms. Advances in Machine Learning I 2010: 121-146
- [r1]Petra Kralj Novak, Nada Lavrac, Geoffrey I. Webb: Supervised Descriptive Rule Induction. Encyclopedia of Machine Learning 2010: 938-941
2000 – 2009
- 2009
- [j41]Petra Kralj Novak, Nada Lavrac, Dragan Gamberger, Antonija Krstacic: CSM-SD: Methodology for contrast set mining through subgroup discovery. Journal of Biomedical Informatics 42(1): 113-122 (2009)
- [j40]Petra Kralj Novak, Nada Lavrac, Geoffrey I. Webb: Supervised Descriptive Rule Discovery: A Unifying Survey of Contrast Set, Emerging Pattern and Subgroup Mining. Journal of Machine Learning Research 10: 377-403 (2009)
- [j39]Filip Zelezný, Nada Lavrac: Guest editors' introduction: Special issue on Inductive Logic Programming (ILP-2008). Machine Learning 76(1): 1-2 (2009)
- 2008
- [j38]Joël Plisson, Nada Lavrac, Dunja Mladenic, Tomaz Erjavec: Ripple Down Rule learning for automated word lemmatisation. AI Commun. 21(1): 15-26 (2008)
- [j37]Igor Trajkovski, Nada Lavrac, Jakub Tolar: SEGS: Search for enriched gene sets in microarray data. Journal of Biomedical Informatics 41(4): 588-601 (2008)
- [j36]Gemma C. Garriga, Petra Kralj, Nada Lavrac: Closed Sets for Labeled Data. Journal of Machine Learning Research 9: 559-580 (2008)
- [j35]Igor Trajkovski, Filip Zelezný, Nada Lavrac, Jakub Tolar: Learning Relational Descriptions of Differentially Expressed Gene Groups. IEEE Transactions on Systems, Man, and Cybernetics, Part C 38(1): 16-25 (2008)
- [c61]Jeroen S. de Bruin, Joost N. Kok, Nada Lavrac, Igor Trajkovski: On the Design of Knowledge Discovery Services Design Patterns and Their Application in a Use Case Implementation. ISoLA 2008: 649-662
- [c60]Blaz Fortuna, Nada Lavrac, Paola Velardi: Advancing Topic Ontology Learning through Term Extraction. PRICAI 2008: 626-635
- [c59]Dragan Gamberger, Nada Lavrac, Johannes Fürnkranz: Handling Unknown and Imprecise Attribute Values in Propositional Rule Learning: A Feature-Based Approach. PRICAI 2008: 636-645
- [e7]Filip Zelezný, Nada Lavrac (Eds.): Inductive Logic Programming, 18th International Conference, ILP 2008, Prague, Czech Republic, September 10-12, 2008, Proceedings. Lecture Notes in Computer Science 5194, Springer 2008, ISBN 978-3-540-85927-7
- 2007
- [j34]Dragan Gamberger, Nada Lavrac, Antonija Krstacic, Goran Krstacic: Clinical data analysis based on iterative subgroup discovery: experiments in brain ischaemia data analysis. Appl. Intell. 27(3): 205-217 (2007)
- [j33]Nada Lavrac, Marko Bohanec, Aleksander Pur, Bojan Cestnik, Marko Debeljak, Andrej Kobler: Data mining and visualization for decision support and modeling of public health-care resources. Journal of Biomedical Informatics 40(4): 438-447 (2007)
- [j32]Nada Lavrac, Peter Ljubic, Tanja Urbani, Gregor Papa, Mitja Jermol, S. Bollhalter: Trust Modeling for Networked Organizations Using Reputation and Collaboration Estimates. IEEE Transactions on Systems, Man, and Cybernetics, Part C 37(3): 429-439 (2007)
- [j31]Joël Plisson, Peter Ljubic, Igor Mozetic, Nada Lavrac: An Ontology for Virtual Organization Breeding Environments. IEEE Transactions on Systems, Man, and Cybernetics, Part C 37(6): 1327-1341 (2007)
- [c58]Petra Kralj, Nada Lavrac, Dragan Gamberger, Antonija Krstacic: Contrast Set Mining for Distinguishing Between Similar Diseases. AIME 2007: 109-118
- [c57]Igor Trajkovski, Nada Lavrac: Interpreting Gene Expression Data by Searching for Enriched Gene Sets. AIME 2007: 144-148
- [c56]Dragan Gamberger, Nada Lavrac: Supporting Factors in Descriptive Analysis of Brain Ischaemia. AIME 2007: 155-159
- [c55]Aleksander Pur, Marko Bohanec, Nada Lavrac, Bojan Cestnik, Marko Debeljak, Anton Gradisek: Monitoring Human Resources of a Public Health-Care System Through Intelligent Data Analysis and Visualization. AIME 2007: 175-179
- [c54]Damjan Demsar, Igor Mozetic, Nada Lavrac: Collaboration Opportunity Finder. Virtual Enterprises and Collaborative Networks 2007: 179-186
- [c53]Igor Trajkovski, Nada Lavrac: Efficient Generation of Biologically Relevant Enriched Gene Sets. ISBRA 2007: 248-259
- [c52]Petra Kralj, Nada Lavrac, Dragan Gamberger, Antonija Krstacic: Contrast Set Mining Through Subgroup Discovery Applied to Brain Ischaemina Data. PAKDD 2007: 579-586
- [e6]Michael R. Berthold, John Shawe-Taylor, Nada Lavrac (Eds.): Advances in Intelligent Data Analysis VII, 7th International Symposium on Intelligent Data Analysis, IDA 2007, Ljubljana, Slovenia, September 6-8, 2007, Proceedings. Lecture Notes in Computer Science 4723, Springer 2007, ISBN 978-3-540-74824-3
- 2006
- [j30]Branko Kavsek, Nada Lavrac: APRIORI-SD: Adapting Association Rule Learning to Subgroup Discovery. Applied Artificial Intelligence 20(7): 543-583 (2006)
- [j29]Filip Zelezný, Nada Lavrac: Propositionalization-based relational subgroup discovery with RSD. Machine Learning 62(1-2): 33-63 (2006)
- [c51]Igor Trajkovski, Filip Zelezný, Jakub Tolar, Nada Lavrac: Relational Subgroup Discovery for Descriptive Analysis of Microarray Data. CompLife 2006: 86-96
- [c50]Monika Záková, Filip Zelezný, Javier A. García-Sedano, Cyril Masia Tissot, Nada Lavrac, Petr Kremen, Javier Molina: Relational Data Mining Applied to Virtual Engineering of Product Designs. ILP 2006: 439-453
- [c49]
- [c48]Igor Trajkovski, Filip Zelezný, Nada Lavrac, Jakub Tolar: Relational Descriptive Analysis of Gene Expression Data. STAIRS 2006: 184-195
- [e5]Ljupco Todorovski, Nada Lavrac, Klaus P. Jantke (Eds.): Discovery Science, 9th International Conference, DS 2006, Barcelona, Spain, October 7-10, 2006, Proceedings. Lecture Notes in Computer Science 4265, Springer 2006, ISBN 3-540-46491-3
- 2005
- [c47]Nada Lavrac, Marko Bohanec, Aleksander Pur, Bojan Cestnik, Mitja Jermol, Tanja Urbancic, Marko Debeljak, Branko Kavsek, Tadeja Kopac: Resource Modeling and Analysis of Regional Public Health Care Data by Means of Knowledge Technologies. AIME 2005: 414-418
- [c46]
- [c45]Aleksander Pur, Marko Bohanec, Bojan Cestnik, Nada Lavrac, Marko Debeljak, Tadeja Kopac: Data Mining for Decision Support: An Application in Public Health Care. IEA/AIE 2005: 459-469
- [c44]Nada Lavrac, Peter Ljubic, Mitja Jermol, Gregor Papa: A Decision Support Approach to Modeling Trust in Networked Organizations. IEA/AIE 2005: 746-748
- [c43]
- [p1]Nada Lavrac, Blaz Zupan: Data Mining in Medicine. The Data Mining and Knowledge Discovery Handbook 2005: 1107-1138
- 2004
- [j28]Dragan Gamberger, Nada Lavrac, Filip Zelezný, Jakub Tolar: Induction of comprehensible models for gene expression datasets by subgroup discovery methodology. Journal of Biomedical Informatics 37(4): 269-284 (2004)
- [j27]Nada Lavrac, Branko Kavsek, Peter A. Flach, Ljupco Todorovski: Subgroup Discovery with CN2-SD. Journal of Machine Learning Research 5: 153-188 (2004)
- [j26]Nada Lavrac, Hiroshi Motoda, Tom Fawcett: Editorial: Data Mining Lessons Learned. Machine Learning 57(1-2): 5-11 (2004)
- [j25]Nada Lavrac, Hiroshi Motoda, Tom Fawcett, Robert Holte, Pat Langley, Pieter W. Adriaans: Introduction: Lessons Learned from Data Mining Applications and Collaborative Problem Solving. Machine Learning 57(1-2): 13-34 (2004)
- [j24]Nada Lavrac, Bojan Cestnik, Dragan Gamberger, Peter A. Flach: Decision Support Through Subgroup Discovery: Three Case Studies and the Lessons Learned. Machine Learning 57(1-2): 115-143 (2004)
- [c42]Nada Lavrac, Dragan Gamberger: Relevancy in Constraint-Based Subgroup Discovery. Constraint-Based Mining and Inductive Databases 2004: 243-266
- [c41]Nada Lavrac, Filip Zelezný, Saso Dzeroski: Local Patterns: Theory and Practice of Constraint-Based Relational Subgroup Discovery. Local Pattern Detection 2004: 71-88
- [c40]Dragan Gamberger, Nada Lavrac: Avoiding Data Overfitting in Scientific Discovery: Experiments in Functional Genomics. ECAI 2004: 470-474
- [c39]Mitja Jermol, Nada Lavrac, Tanja Urbancic, Tadeja Kopac: Supporting a Public Health Care Virtual Organization by Knowledge Technologies. Virtual Enterprises and Collaborative Networks 2004: 567-576
- [c38]Branko Kavsek, Nada Lavrac, Ljupco Todorovski: ROC Analysis of Example Weighting in Subgroup Discovery. ROCAI 2004: 55-60
- 2003
- [j23]Dragan Gamberger, Nada Lavrac: Active subgroup mining: a case study in coronary heart disease risk group detection. Artificial Intelligence in Medicine 28(1): 27-57 (2003)
- [j22]Mitja Jermol, Nada Lavrac, Tanja Urbancic: Managing business intelligence in a virtual enterprise: A case study and knowledge management lessons learned. Journal of Intelligent and Fuzzy Systems 14(3): 121-136 (2003)
- [c37]Dragan Gamberger, Nada Lavrac: Analysis of Gene Expression Data by the Logic Minimization Approach. AIME 2003: 244-248
- [c36]Branko Kavsek, Nada Lavrac, Viktor Jovanoski: APRIORI-SD: Adapting Association Rule Learning to Subgroup Discovery. IDA 2003: 230-241
- [c35]Mark-A. Krogel, Simon Rawles, Filip Zelezný, Peter A. Flach, Nada Lavrac, Stefan Wrobel: Comparative Evaluation of Approaches to Propositionalization. ILP 2003: 197-214
- [e4]Nada Lavrac, Dragan Gamberger, Ljupco Todorovski, Hendrik Blockeel (Eds.): Machine Learning: ECML 2003, 14th European Conference on Machine Learning, Cavtat-Dubrovnik, Croatia, September 22-26, 2003, Proceedings. Lecture Notes in Computer Science 2837, Springer 2003, ISBN 3-540-20121-1
- [e3]Nada Lavrac, Dragan Gamberger, Hendrik Blockeel, Ljupco Todorovski (Eds.): Knowledge Discovery in Databases: PKDD 2003, 7th European Conference on Principles and Practice of Knowledge Discovery in Databases, Cavtat-Dubrovnik, Croatia, September 22-26, 2003, Proceedings. Lecture Notes in Computer Science 2838, Springer 2003, ISBN 3-540-20085-1
- 2002
- [j21]Dragan Gamberger, Nada Lavrac: Expert-Guided Subgroup Discovery: Methodology and Application. J. Artif. Intell. Res. (JAIR) 17: 501-527 (2002)
- [j20]Dragan Gamberger, Nada Lavrac, Goran Krstacic: Confirmation rule induction and its applications to coronary heart disease diagnosis and risk group discovery. Journal of Intelligent and Fuzzy Systems 12(1): 35-48 (2002)
- [c34]Peter A. Flach, Nada Lavrac: Learning in Clausal Logic: A Perspective on Inductive Logic Programming. Computational Logic: Logic Programming and Beyond 2002: 437-471
- [c33]Nada Lavrac, Peter A. Flach, Branko Kavsek, Ljupco Todorovski: Adapting classification rule induction to subgroup discovery. ICDM 2002: 266-273
- [c32]Dragan Gamberger, Nada Lavrac: Descriptive Induction through Subgroup Discovery: A Case Study in a Medical Domain. ICML 2002: 163-170
- [c31]
- [c30]Nada Lavrac, Filip Zelezný, Peter A. Flach: RSD: Relational Subgroup Discovery through First-Order Feature Construction. ILP 2002: 149-165
- [c29]Dragan Gamberger, Nada Lavrac: Generating Actionable Knowledge by Expert-Guided Subgroup Discovery. PKDD 2002: 163-174
- 2001
- [j19]Elpida T. Keravnou, Nada Lavrac: AIM portraits: tracing the evolution of artificial intelligence in medicine and predicting its future in the new millennium. Artificial Intelligence in Medicine 23(1): 1-4 (2001)
- [j18]Nada Lavrac, Peter A. Flach: An extended transformation approach to inductive logic programming. ACM Trans. Comput. Log. 2(4): 458-494 (2001)
- [c28]Branko Kavsek, Nada Lavrac, Anuska Ferligoj: Consensus Decision Trees: Using Consensus Hierarchical Clustering for Data Relabelling and Reduction. ECML 2001: 251-262
- [c27]
- 2000
- [j17]Dragan Gamberger, Nada Lavrac, Saso Dzeroski: Noise Detection and Elimination in data Proprocessing: Experiments in Medical Domains. Applied Artificial Intelligence 14(2): 205-223 (2000)
- [c26]Dragan Gamberger, Nada Lavrac, Goran Krstacic, Tomislav Smuc: Inconsistency Tests for Patient Records in a Coronary Heart Disease Database. ISMDA 2000: 183-189
- [c25]
- [c24]Ljupco Todorovski, Peter A. Flach, Nada Lavrac: Predictive Performance of Weghted Relative Accuracy. PKDD 2000: 255-264
1990 – 1999
- 1999
- [j16]Nada Lavrac: Selected techniques for data mining in medicine. Artificial Intelligence in Medicine 16(1): 3-23 (1999)
- [j15]
- [j14]Nada Lavrac, Dragan Gamberger, Viktor Jovanoski: A Study of Relevance for Learning in Deductive Databases. J. Log. Program. 40(2-3): 215-249 (1999)
- [j13]Nada Lavrac, Saso Dzeroski, Masayuki Numao: Inductive Logic Programming for Relational Knowledge Discovery. New Generation Comput. 17(1): 3-23 (1999)
- [c23]
- [c22]Dragan Gamberger, Nada Lavrac, Ciril Groselj: Diagnostic Rules of Increased Reliability for Critical Medical Applications. AIMDM 1999: 361-365
- [c21]
- [c20]Dragan Gamberger, Nada Lavrac, Ciril Groselj: Experiments with Noise Filtering in a Medical Domain. ICML 1999: 143-151
- [c19]Nada Lavrac, Peter A. Flach, Blaz Zupan: Rule Evaluation Measures: A Unifying View. ILP 1999: 174-185
- 1998
- [j12]Nada Lavrac, Blaz Zupan, Igor Kononenko, Matjaz Kukar, Elpida T. Keravnou: Intelligent Data Analysis for Medical Diagnosis: Using Machine Learning and Temporal Abstraction. AI Commun. 11(3-4): 191-218 (1998)
- [j11]Nada Lavrac, Dragan Gamberger, Peter D. Turney: A Relevancy Filter for Constructive Induction. IEEE Intelligent Systems 13(2): 50-56 (1998)
- [c18]
- 1997
- [j10]Darko Zupanic, Milan Hodoscek, Nada Lavrac, Igor Mozetic: Global Energy Minimization of Small Molecules Combining Constraint Logic Programming and Molecular Mechanics. Journal of Chemical Information and Computer Sciences 37(6): 966-970 (1997)
- [c17]Igor Zelic, Igor Kononenko, Nada Lavrac, Vanja Vuga: Machine Learning Applied to Diagnosis of Sport Injuries. AIME 1997: 138-141
- [c16]Igor Zelic, Igor Kononenko, Nada Lavrac, Vanja Vuga: Diagnosis of sport injuries with machine learning: explanation of induced decisions. CBMS 1997: 195-199
- [c15]Iztok A. Pilih, Dunja Mladenic, Nada Lavrac, Tine S. Prevec: Using machine learning for outcome prediction of patients with severe head injury. CBMS 1997: 200-204
- [c14]Dragan Gamberger, Nada Lavrac: Conditions for Occam's Razor Applicability and Noise Elimination. ECML 1997: 108-123
- [e2]Nada Lavrac, Saso Dzeroski (Eds.): Inductive Logic Programming, 7th International Workshop, ILP-97, Prague, Czech Republic, September 17-20, 1997, Proceedings. Lecture Notes in Computer Science 1297, Springer 1997, ISBN 3-540-63514-9
- 1996
- [j9]Nada Lavrac, Irene Weber, Darko Zupanic, Dimitar Kazakov, Olga Stepánková, Saso Dzeroski: ILPNET Repositories on WWW: Inductive Logic Programming Systems, Datasets and Bibliography. AI Commun. 9(4): 157-206 (1996)
- [j8]Luc De Raedt, Nada Lavrac: Multiple Predicate Learning in Two Inductive Logic Programming Settings. Logic Journal of the IGPL 4(2): 227-254 (1996)
- [j7]Nada Lavrac, Stefan Wrobel: Induktive Logikprogrammierung - Grundlagen und Techniken. KI 10(3): 46-54 (1996)
- [j6]Nada Lavrac, Saso Dzeroski: A Reply to Pazzani's Book Review of "Inductive Logic Programming: Techniques and Applications". Machine Learning 23(1): 109-111 (1996)
- [c13]Nada Lavrac, Dragan Gamberger, Peter D. Turney: Cost-Sensitive Feature Reduction Applied to a Hybrid Genetic Algorithm. ALT 1996: 127-134
- [c12]Dragan Gamberger, Nada Lavrac, Saso Dzeroski: Noise Elimination in Inductive Concept Learning: A Case Study in Medical Diagnosois. ALT 1996: 199-212
- [c11]Dragan Gamberger, Nada Lavrac: Noise Detection and Elimination Applied to Noise Handling in a KRK Chess Endgame. Inductive Logic Programming Workshop 1996: 72-88
- 1995
- [j5]Nada Lavrac, Luc De Raedt: Inductive Logic Programming: A Survey of European Research. AI Commun. 8(1): 3-19 (1995)
- [e1]Nada Lavrac, Stefan Wrobel (Eds.): Machine Learning: ECML-95, 8th European Conference on Machine Learning, Heraclion, Crete, Greece, April 25-27, 1995, Proceedings. Lecture Notes in Computer Science 912, Springer 1995, ISBN 3-540-59286-5
- 1994
- [b2]Nada Lavrac, Saso Dzeroski: Inductive logic programming - techniques and applications. Ellis Horwood series in artificial intelligence, Ellis Horwood 1994, ISBN 978-0-13-457870-5, pp. I-XIX, 1-293
- [j4]Nada Lavrac, Saso Dzeroski: Weakening the language bias in LINUS. J. Exp. Theor. Artif. Intell. 6(1): 95-119 (1994)
- [c10]
- 1993
- [j3]Nada Lavrac, Saso Dzeroski, Vladimir Pirnat, Viljem Krizman: The utility of background knowledge in learning medical diagnostic rules. Applied Artificial Intelligence 7(3): 273-293 (1993)
- [j2]Saso Dzeroski, Nada Lavrac: Inductive Learning in Deductive Databases. IEEE Trans. Knowl. Data Eng. 5(6): 939-949 (1993)
- [c9]
- [c8]
- 1992
- [c7]Nada Lavrac, Saso Dzeroski: Background Knowledge and Declarative Bias in Inductive Concept Learning. AII 1992: 51-71
- [c6]Matevz Kovacic, Nada Lavrac, Marko Grobelnik, Darko Zupanic, Dunja Mladenic: Stochastic Search in Inductive Logic Programming. ECAI 1992: 444-445
- 1991
- [c5]Nada Lavrac, Saso Dzeroski, Marko Grobelnik: Learning Nonrecursive Definitions of Relations with LINUS. EWSL 1991: 265-281
- [c4]Saso Dzeroski, Nada Lavrac: Learning Relations from Noisy Examples: An Empirical Comparison of LINUS and FOIL. ML 1991: 399-402
- [c3]Nada Lavrac, Saso Dzeroski, Vladimir Pirnat, Viljem Krizman: Learning Rules for Early Diagnosis of Rheumatic Diseases. SCAI 1991: 138-149
1980 – 1989
- 1989
- [b1]Ivan Bratko, Igor Mozetic, Nada Lavrac: KARDIO - a study in deep and qualitative knowledge for expert systems. MIT Press 1989, ISBN 978-0-262-02273-6, pp. I-XIV, 1-260
- [j1]Nada Lavrac, Igor Mozetic: Methods for knowledge acquisition and refinement in second generation expert systems. SIGART Newsletter 108: 63-69 (1989)
- 1987
- [c2]Matjaz Gams, Nada Lavrac: Review of Five Empirical Learning Systems Within a Proposed Schemata. EWSL 1987: 46-66
- 1986
- [c1]Ryszard S. Michalski, Igor Mozetic, Jiarong Hong, Nada Lavrac: The Multi-Purpose Incremental Learning System AQ15 and Its Testing Application to Three Medical Domains. AAAI 1986: 1041-1047
Coauthor Index
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last updated on 2013-10-02 11:01 CEST by the dblp team