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Nada Lavrac Vis

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*2009
105EEPetra 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)
2008
104 Filip Zelezný, Nada Lavrac: Inductive Logic Programming, 18th International Conference, ILP 2008, Prague, Czech Republic, September 10-12, 2008, Proceedings Springer 2008
103EEJeroen 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
102EEBlaz Fortuna, Nada Lavrac, Paola Velardi: Advancing Topic Ontology Learning through Term Extraction. PRICAI 2008: 626-635
101EEDragan Gamberger, Nada Lavrac, Johannes Fürnkranz: Handling Unknown and Imprecise Attribute Values in Propositional Rule Learning: A Feature-Based Approach. PRICAI 2008: 636-645
100EEJoël Plisson, Nada Lavrac, Dunja Mladenic, Tomaz Erjavec: Ripple Down Rule learning for automated word lemmatisation. AI Commun. 21(1): 15-26 (2008)
99EEIgor 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)
98EEIgor Trajkovski, Nada Lavrac, Jakub Tolar: SEGS: Search for enriched gene sets in microarray data. Journal of Biomedical Informatics 41(4): 588-601 (2008)
2007
97 Michael R. Berthold, John Shawe-Taylor, Nada Lavrac: Advances in Intelligent Data Analysis VII, 7th International Symposium on Intelligent Data Analysis, IDA 2007, Ljubljana, Slovenia, September 6-8, 2007, Proceedings Springer 2007
96EEPetra Kralj, Nada Lavrac, Dragan Gamberger, Antonija Krstacic: Contrast Set Mining for Distinguishing Between Similar Diseases. AIME 2007: 109-118
95EEIgor Trajkovski, Nada Lavrac: Interpreting Gene Expression Data by Searching for Enriched Gene Sets. AIME 2007: 144-148
94EEDragan Gamberger, Nada Lavrac: Supporting Factors in Descriptive Analysis of Brain Ischaemia. AIME 2007: 155-159
93EEAleksander 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
92EEIgor Trajkovski, Nada Lavrac: Efficient Generation of Biologically Relevant Enriched Gene Sets. ISBRA 2007: 248-259
91EEPetra Kralj, Nada Lavrac, Dragan Gamberger, Antonija Krstacic: Contrast Set Mining Through Subgroup Discovery Applied to Brain Ischaemina Data. PAKDD 2007: 579-586
90EEDamjan Demsar, Igor Mozetic, Nada Lavrac: Collaboration Opportunity Finder. Virtual Enterprises and Collaborative Networks 2007: 179-186
89EEDragan 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)
88EENada 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)
87EEJoël 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)
86EENada 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)
2006
85 Ljupco Todorovski, Nada Lavrac, Klaus P. Jantke: Discovery Science, 9th International Conference, DS 2006, Barcelona, Spain, October 7-10, 2006, Proceedings Springer 2006
84EEIgor Trajkovski, Filip Zelezný, Jakub Tolar, Nada Lavrac: Relational Subgroup Discovery for Descriptive Analysis of Microarray Data. CompLife 2006: 86-96
83EEMonika Záková, Filip Zelezný, Javier A. Garcia-Sedano, Cyril Masia Tissot, Nada Lavrac, Petr Kremen, Javier Molina: Relational Data Mining Applied to Virtual Engineering of Product Designs. ILP 2006: 439-453
82EEGemma C. Garriga, Petra Kralj, Nada Lavrac: Closed Sets for Labeled Data. PKDD 2006: 163-174
81 Igor Trajkovski, Filip Zelezný, Nada Lavrac, Jakub Tolar: Relational Descriptive Analysis of Gene Expression Data. STAIRS 2006: 184-195
80EEBranko Kavsek, Nada Lavrac: APRIORI-SD: Adapting Association Rule Learning to Subgroup Discovery. Applied Artificial Intelligence 20(7): 543-583 (2006)
79EEFilip Zelezný, Nada Lavrac: Propositionalization-based relational subgroup discovery with RSD. Machine Learning 62(1-2): 33-63 (2006)
2005
78EENada 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
77EENada Lavrac: SolEuNet: Selected Data Mining Techniques and Applications. GfKl 2005: 32-39
76EEAleksander 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
75EENada Lavrac, Peter Ljubic, Mitja Jermol, Gregor Papa: A Decision Support Approach to Modeling Trust in Networked Organizations. IEA/AIE 2005: 746-748
74EENada Lavrac: Subgroup Discovery Techniques and Applications. PAKDD 2005: 2-14
73 Nada Lavrac, Blaz Zupan: Data Mining in Medicine. The Data Mining and Knowledge Discovery Handbook 2005: 1107-1138
2004
72EENada Lavrac, Dragan Gamberger: Relevancy in Constraint-Based Subgroup Discovery. Constraint-Based Mining and Inductive Databases 2004: 243-266
71 Dragan Gamberger, Nada Lavrac: Avoiding Data Overfitting in Scientific Discovery: Experiments in Functional Genomics. ECAI 2004: 470-474
70EENada Lavrac, Filip Zelezný, Saso Dzeroski: Local Patterns: Theory and Practice of Constraint-Based Relational Subgroup Discovery. Local Pattern Detection 2004: 71-88
69 Branko Kavsek, Nada Lavrac, Ljupco Todorovski: ROC Analysis of Example Weighting in Subgroup Discovery. ROCAI 2004: 55-60
68 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
67EEDragan 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)
66EENada Lavrac, Branko Kavsek, Peter A. Flach, Ljupco Todorovski: Subgroup Discovery with CN2-SD. Journal of Machine Learning Research 5: 153-188 (2004)
65EENada 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)
64EENada 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)
63EENada Lavrac, Hiroshi Motoda, Tom Fawcett: Editorial: Data Mining Lessons Learned. Machine Learning 57(1-2): 5-11 (2004)
2003
62 Nada Lavrac, Dragan Gamberger, Ljupco Todorovski, Hendrik Blockeel: Machine Learning: ECML 2003, 14th European Conference on Machine Learning, Cavtat-Dubrovnik, Croatia, September 22-26, 2003, Proceedings Springer 2003
61 Nada Lavrac, Dragan Gamberger, Hendrik Blockeel, Ljupco Todorovski: 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 Springer 2003
60EEDragan Gamberger, Nada Lavrac: Analysis of Gene Expression Data by the Logic Minimization Approach. AIME 2003: 244-248
59EEBranko Kavsek, Nada Lavrac, Viktor Jovanoski: APRIORI-SD: Adapting Association Rule Learning to Subgroup Discovery. IDA 2003: 230-241
58EEMark-A. Krogel, Simon Rawles, Filip Zelezný, Peter A. Flach, Nada Lavrac, Stefan Wrobel: Comparative Evaluation of Approaches to Propositionalization. ILP 2003: 197-214
57EEDragan 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)
56EEMitja 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)
2002
55EEPeter A. Flach, Nada Lavrac: Learning in Clausal Logic: A Perspective on Inductive Logic Programming. Computational Logic: Logic Programming and Beyond 2002: 437-471
54EENada Lavrac, Peter A. Flach, Branko Kavsek, Ljupco Todorovski: Adapting classification rule induction to subgroup discovery. ICDM 2002: 266-273
53 Dragan Gamberger, Nada Lavrac: Descriptive Induction through Subgroup Discovery: A Case Study in a Medical Domain. ICML 2002: 163-170
52EENada Lavrac, Filip Zelezný, Peter A. Flach: RSD: Relational Subgroup Discovery through First-Order Feature Construction. ILP 2002: 149-165
51EEDragan Gamberger, Nada Lavrac: Generating Actionable Knowledge by Expert-Guided Subgroup Discovery. PKDD 2002: 163-174
50 Nada Lavrac: Virtual Enterprise for Data Mining and Decision Support. PRO-VE 2002
49EEDragan Gamberger, Nada Lavrac: Expert-Guided Subgroup Discovery: Methodology and Application. J. Artif. Intell. Res. (JAIR) 17: 501-527 (2002)
48EEDragan 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)
2001
47EEBranko Kavsek, Nada Lavrac, Anuska Ferligoj: Consensus Decision Trees: Using Consensus Hierarchical Clustering for Data Relabelling and Reduction. ECML 2001: 251-262
46EEViktor Jovanoski, Nada Lavrac: Classification Rule Learning with APRIORI-C. EPIA 2001: 44-51
45EENada Lavrac, Peter A. Flach: An extended transformation approach to inductive logic programming. ACM Trans. Comput. Log. 2(4): 458-494 (2001)
44 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)
2000
43EEDragan Gamberger, Nada Lavrac, Goran Krstacic, Tomislav Smuc: Inconsistency Tests for Patient Records in a Coronary Heart Disease Database. ISMDA 2000: 183-189
42EELjupco Todorovski, Peter A. Flach, Nada Lavrac: Predictive Performance of Weghted Relative Accuracy. PKDD 2000: 255-264
41EEDragan Gamberger, Nada Lavrac: Confirmation Rule Sets. PKDD 2000: 34-43
40 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)
1999
39EEDragan Gamberger, Nada Lavrac, Ciril Groselj: Diagnostic Rules of Increased Reliability for Critical Medical Applications. AIMDM 1999: 361-365
38EENada Lavrac: Machine Learning for Data Mining in Medicine. AIMDM 1999: 47-64
37 Nada Lavrac: Challenges for Inductive Logic Programming. EPIA 1999: 16-33
36 Dragan Gamberger, Nada Lavrac, Ciril Groselj: Experiments with Noise Filtering in a Medical Domain. ICML 1999: 143-151
35EENada Lavrac, Peter A. Flach, Blaz Zupan: Rule Evaluation Measures: A Unifying View. ILP 1999: 174-185
34 Nada Lavrac: Selected techniques for data mining in medicine. Artificial Intelligence in Medicine 16(1): 3-23 (1999)
33 Saso Dzeroski, Nada Lavrac: Editorial. Data Min. Knowl. Discov. 3(1): 5-6 (1999)
32 Nada Lavrac, Dragan Gamberger, Viktor Jovanoski: A Study of Relevance for Learning in Deductive Databases. J. Log. Program. 40(2-3): 215-249 (1999)
31 Nada Lavrac, Saso Dzeroski, Masayuki Numao: Inductive Logic Programming for Relational Knowledge Discovery. New Generation Comput. 17(1): 3-23 (1999)
1998
30 Nada Lavrac: Inductive Logic Programming for Relational Knowledge Discovery. IJCSLP 1998: 7-24
29 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)
28 Nada Lavrac, Dragan Gamberger, Peter D. Turney: A Relevancy Filter for Constructive Induction. IEEE Intelligent Systems 13(2): 50-56 (1998)
1997
27 Nada Lavrac, Saso Dzeroski: Inductive Logic Programming, 7th International Workshop, ILP-97, Prague, Czech Republic, September 17-20, 1997, Proceedings Springer 1997
26 Igor Zelic, Igor Kononenko, Nada Lavrac, Vanja Vuga: Machine Learning Applied to Diagnosis of Sport Injuries. AIME 1997: 138-141
25EEIgor Zelic, Igor Kononenko, Nada Lavrac, Vanja Vuga: Diagnosis of sport injuries with machine learning: explanation of induced decisions. CBMS 1997: 195-199
24EEIztok 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
23EEDragan Gamberger, Nada Lavrac: Conditions for Occam's Razor Applicability and Noise Elimination. ECML 1997: 108-123
22EEDarko 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)
1996
21 Nada Lavrac, Dragan Gamberger, Peter D. Turney: Cost-Sensitive Feature Reduction Applied to a Hybrid Genetic Algorithm. ALT 1996: 127-134
20 Dragan Gamberger, Nada Lavrac, Saso Dzeroski: Noise Elimination in Inductive Concept Learning: A Case Study in Medical Diagnosois. ALT 1996: 199-212
19 Dragan Gamberger, Nada Lavrac: Noise Detection and Elimination Applied to Noise Handling in a KRK Chess Endgame. Inductive Logic Programming Workshop 1996: 72-88
18 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)
17 Nada Lavrac, Stefan Wrobel: Induktive Logikprogrammierung - Grundlagen und Techniken. KI 10(3): 46-54 (1996)
16EELuc De Raedt, Nada Lavrac: Multiple Predicate Learning in Two Inductive Logic Programming Settings. Logic Journal of the IGPL 4(2): 227-254 (1996)
15 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)
1995
14 Nada Lavrac, Stefan Wrobel: Machine Learning: ECML-95, 8th European Conference on Machine Learning, Heraclion, Crete, Greece, April 25-27, 1995, Proceedings Springer 1995
13 Nada Lavrac, Luc De Raedt: Inductive Logic Programming: A Survey of European Research. AI Commun. 8(1): 3-19 (1995)
1994
12 Nada Lavrac: Inductive Logic Programming. WLP 1994: 146-160
1993
11 Luc De Raedt, Nada Lavrac, Saso Dzeroski: Multiple Predicate Learning. IJCAI 1993: 1037-1043
10EELuc De Raedt, Nada Lavrac: The Many Faces of Inductive Logic Programming. ISMIS 1993: 435-449
9 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)
8EESaso Dzeroski, Nada Lavrac: Inductive Learning in Deductive Databases. IEEE Trans. Knowl. Data Eng. 5(6): 939-949 (1993)
1992
7 Nada Lavrac, Saso Dzeroski: Background Knowledge and Declarative Bias in Inductive Concept Learning. AII 1992: 51-71
6 Matevz Kovacic, Nada Lavrac, Marko Grobelnik, Darko Zupanic, Dunja Mladenic: Stochastic Search in Inductive Logic Programming. ECAI 1992: 444-445
1991
5EENada Lavrac, Saso Dzeroski, Marko Grobelnik: Learning Nonrecursive Definitions of Relations with LINUS. EWSL 1991: 265-281
4 Saso Dzeroski, Nada Lavrac: Learning Relations from Noisy Examples: An Empirical Comparison of LINUS and FOIL. ML 1991: 399-402
3 Nada Lavrac, Saso Dzeroski, Vladimir Pirnat, Viljem Krizman: Learning Rules for Early Diagnosis of Rheumatic Diseases. SCAI 1991: 138-149
1987
2 Matjaz Gams, Nada Lavrac: Review of Five Empirical Learning Systems Within a Proposed Schemata. EWSL 1987: 46-66
1986
1 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

1Pieter W. Adriaans [64]
2Michael R. Berthold [97]
3Hendrik Blockeel [61] [62]
4Marko Bohanec [76] [78] [86] [93]
5S. Bollhalter [88]
6Jeroen S. de Bruin [103]
7Bojan Cestnik [65] [76] [78] [86] [93]
8Marko Debeljak [76] [78] [86] [93]
9Damjan Demsar [90]
10Saso Dzeroski [3] [4] [5] [7] [8] [9] [11] [15] [18] [20] [27] [31] [33] [40] [70]
11Tomaz Erjavec [100]
12Tom Fawcett [63] [64]
13Anuska Ferligoj [47]
14Peter A. Flach [35] [42] [45] [52] [54] [55] [58] [65] [66]
15Blaz Fortuna [102]
16Johannes Fürnkranz [101]
17Dragan Gamberger [19] [20] [21] [23] [28] [32] [36] [39] [40] [41] [43] [48] [49] [51] [53] [57] [60] [61] [62] [65] [67] [71] [72] [89] [91] [94] [96] [101] [105]
18Matjaz Gams [2]
19Javier A. Garcia-Sedano [83]
20Gemma C. Garriga (Gemma Casas-Garriga) [82]
21Anton Gradisek [93]
22Marko Grobelnik [5] [6]
23Ciril Groselj [36] [39]
24Milan Hodoscek [22]
25Robert C. Holte (Robert Holte) [64]
26Jiarong Hong [1]
27Klaus P. Jantke [85]
28Mitja Jermol [56] [68] [75] [78] [88]
29Viktor Jovanoski [32] [46] [59]
30Branko Kavsek [47] [54] [59] [66] [69] [78] [80]
31Dimitar Kazakov [18]
32Elpida T. Keravnou [29] [44]
33Andrej Kobler [86]
34Joost N. Kok [103]
35Igor Kononenko [25] [26] [29]
36Tadeja Kopac [68] [76] [78]
37Matevz Kovacic [6]
38Petr Kremen [83]
39Viljem Krizman [3] [9]
40Mark-A. Krogel [58]
41Antonija Krstacic [89] [91] [96] [105]
42Goran Krstacic [43] [48] [89]
43Matjaz Kukar [29]
44Pat Langley [64]
45Peter Ljubic [75] [87] [88]
46Ryszard S. Michalski [1]
47Dunja Mladenic [6] [24] [100]
48Javier Molina [83]
49Hiroshi Motoda [63] [64]
50Igor Mozetic [1] [22] [87] [90]
51Petra Kralj Novak (Petra Kralj) [82] [91] [96] [105]
52Masayuki Numao [31]
53Gregor Papa [75] [88]
54Iztok A. Pilih [24]
55Vladimir Pirnat [3] [9]
56Joël Plisson [87] [100]
57Tine S. Prevec [24]
58Aleksander Pur [76] [78] [86] [93]
59Luc De Raedt [10] [11] [13] [16]
60Simon Rawles [58]
61John Shawe-Taylor [97]
62Tomislav Smuc [43]
63Olga Stepánková [18]
64Cyril Masia Tissot [83]
65Ljupco Todorovski [42] [54] [61] [62] [66] [69] [85]
66Jakub Tolar [67] [81] [84] [98] [99]
67Igor Trajkovski [81] [84] [92] [95] [98] [99] [103]
68Peter D. Turney [21] [28]
69Tanja Urbancic [56] [68] [78]
70Tanja Urbani [88]
71Paola Velardi [102]
72Vanja Vuga [25] [26]
73Irene Weber [18]
74Stefan Wrobel [14] [17] [58]
75Monika Záková [83]
76Filip Zelezný [52] [58] [67] [70] [79] [81] [83] [84] [99] [104]
77Igor Zelic [25] [26]
78Blaz Zupan [29] [35] [73]
79Darko Zupanic [6] [18] [22]

Copyright © Tue Nov 3 08:52:44 2009 by Michael Ley (ley@uni-trier.de)