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*2009
124EEPance Panov, Larisa N. Soldatova, Saso Dzeroski: Towards an Ontology of Data Mining Investigations. Discovery Science 2009: 257-271
123EEAndreja Naumoski, Dragi Kocev, Natasa Atanasova, Kosta Mitreski, Svetislav Krstic, Saso Dzeroski: Predicting chemical parameters of the water from diatom abudance in lake Prespa and its tributaries. ITEE 2009: 264-277
122EESaso Dzeroski, Pance Panov, Bernard Zenko: Machine Learning, Ensemble Methods in. Encyclopedia of Complexity and Systems Science 2009: 5317-5325
2008
121EEPance Panov, Saso Dzeroski, Larisa N. Soldatova: OntoDM: An Ontology of Data Mining. ICDM Workshops 2008: 752-760
120EEAleksandar Peckov, Saso Dzeroski, Ljupco Todorovski: A Minimal Description Length Scheme for Polynomial Regression. PAKDD 2008: 284-295
119EEBernard Zenko, Saso Dzeroski: Learning Classification Rules for Multiple Target Attributes. PAKDD 2008: 454-465
118EEWill Bridewell, Pat Langley, Ljupco Todorovski, Saso Dzeroski: Inductive process modeling. Machine Learning 71(1): 1-32 (2008)
117EECeline Vens, Jan Struyf, Leander Schietgat, Saso Dzeroski, Hendrik Blockeel: Decision trees for hierarchical multi-label classification. Machine Learning 73(2): 185-214 (2008)
2007
116 Saso Dzeroski, Ljupco Todorovski: Computational Discovery of Scientific Knowledge, Introduction, Techniques, and Applications in Environmental and Life Sciences Springer 2007
115 Saso Dzeroski, Jan Struyf: Knowledge Discovery in Inductive Databases, 5th International Workshop, KDID 2006, Berlin, Germany, September 18, 2006, Revised Selected and Invited Papers Springer 2007
114EESaso Dzeroski, Pat Langley, Ljupco Todorovski: Computational Discovery of Scientific Knowledge. Computational Discovery of Scientific Knowledge 2007: 1-14
113EEDimitar Hristovski, Borut Peterlin, Saso Dzeroski, Janez Stare: Literature Based Discovery Support System and Its Application to Disease Gene Identification. Computational Discovery of Scientific Knowledge 2007: 307-326
112EELjupco Todorovski, Saso Dzeroski: Integrating Domain Knowledge in Equation Discovery. Computational Discovery of Scientific Knowledge 2007: 69-97
111EEJan Struyf, Saso Dzeroski: Clustering Trees with Instance Level Constraints. ECML 2007: 359-370
110EEAnnalisa Appice, Saso Dzeroski: Stepwise Induction of Multi-target Model Trees. ECML 2007: 502-509
109EEDragi Kocev, Celine Vens, Jan Struyf, Saso Dzeroski: Ensembles of Multi-Objective Decision Trees. ECML 2007: 624-631
108EEPance Panov, Saso Dzeroski: Combining Bagging and Random Subspaces to Create Better Ensembles. IDA 2007: 118-129
107 Annalisa Appice, Saso Dzeroski: Inducing Multi-Target Model Trees in a Stepwise Fashion. SEBD 2007: 16-27
106EEKaterina Taskova, Daniela Stojanova, Marko Bohanec, Saso Dzeroski: A Qualitative Decision-Support Model for Evaluating Researchers. Informatica (Slovenia) 31(4): 479-486 (2007)
105EESaso Dzeroski, Jan Struyf: 5th international workshop on knowledge discovery in inductive databases (KDID'06): workshop report. SIGKDD Explorations 9(1): 56-58 (2007)
2006
104EETaneli Mielikäinen, Pance Panov, Saso Dzeroski: Itemset Support Queries Using Frequent Itemsets and Their Condensed Representations. Discovery Science 2006: 161-172
103EESaso Dzeroski: From Inductive Logic Programming to Relational Data Mining. JELIA 2006: 1-14
102EEDragi Kocev, Jan Struyf, Saso Dzeroski: Beam Search Induction and Similarity Constraints for Predictive Clustering Trees. KDID 2006: 134-151
101EESaso Dzeroski: Towards a General Framework for Data Mining. KDID 2006: 259-300
100EESaso Dzeroski, Valentin Gjorgjioski, Ivica Slavkov, Jan Struyf: Analysis of Time Series Data with Predictive Clustering Trees. KDID 2006: 63-80
99EEHendrik Blockeel, Leander Schietgat, Jan Struyf, Saso Dzeroski, Amanda Clare: Decision Trees for Hierarchical Multilabel Classification: A Case Study in Functional Genomics. PKDD 2006: 18-29
98EEAnneleen Van Assche, Celine Vens, Hendrik Blockeel, Saso Dzeroski: First order random forests: Learning relational classifiers with complex aggregates. Machine Learning 64(1-3): 149-182 (2006)
2005
97 Kurt Driessens, Saso Dzeroski: Combining Model-Based and Instance-Based Learning for First Order Regression. BNAIC 2005: 341-342
96EEJan Struyf, Saso Dzeroski, Hendrik Blockeel, Amanda Clare: Hierarchical Multi-classification with Predictive Clustering Trees in Functional Genomics. EPIA 2005: 272-283
95EEKurt Driessens, Saso Dzeroski: Combining model-based and instance-based learning for first order regression. ICML 2005: 193-200
94EEJan Struyf, Saso Dzeroski: Constraint Based Induction of Multi-objective Regression Trees. KDID 2005: 222-233
93EEBernard Zenko, Saso Dzeroski, Jan Struyf: Learning Predictive Clustering Rules. KDID 2005: 234-250
92 Saso Dzeroski: Relational Data Mining. The Data Mining and Knowledge Discovery Handbook 2005: 869-898
91EEHendrik Blockeel, Saso Dzeroski: Multi-Relational Data Mining 2005: workshop report. SIGKDD Explorations 7(2): 126-128 (2005)
2004
90EESaso Dzeroski, Ljupco Todorovski, Peter Ljubic: Inductive Queries on Polynomial Equations. Constraint-Based Mining and Inductive Databases 2004: 127-154
89EESaso Dzeroski, Ljupco Todorovski, Peter Ljubic: Inductive Databases of Polynomial Equations. DaWaK 2004: 159-168
88EELjupco Todorovski, Peter Ljubic, Saso Dzeroski: Inducing Polynomial Equations for Regression. ECML 2004: 441-452
87EECeline Vens, Anneleen Van Assche, Hendrik Blockeel, Saso Dzeroski: First Order Random Forests with Complex Aggregates. ILP 2004: 323-340
86EENada Lavrac, Filip Zelezný, Saso Dzeroski: Local Patterns: Theory and Practice of Constraint-Based Relational Subgroup Discovery. Local Pattern Detection 2004: 71-88
85EETomaz Erjavec, Saso Dzeroski: Machine Learning of Morphosyntactic Structure: Lemmatizing Unknown Slovene Words. Applied Artificial Intelligence 18(1): 17-41 (2004)
84EEHendrik Blockeel, Saso Dzeroski, Boris Kompare, Stefan Kramer, Bernhard Pfahringer, Wim Van Laer: Experiments In Predicting Biodegradability. Applied Artificial Intelligence 18(2): 157-181 (2004)
83EESaso Dzeroski, Bernard Zenko: Is Combining Classifiers with Stacking Better than Selecting the Best One? Machine Learning 54(3): 255-273 (2004)
82EEKurt Driessens, Saso Dzeroski: Integrating Guidance into Relational Reinforcement Learning. Machine Learning 57(3): 271-304 (2004)
81EESaso Dzeroski, Hendrik Blockeel: Multi-relational data mining 2004: workshop report. SIGKDD Explorations 6(2): 140-141 (2004)
80EESaso Dzeroski, Bernard Zenko, Marko Debeljak: A report on the fourth international workshop on environmental applications of machine learning (EAML 2004). SIGKDD Explorations 6(2): 155-156 (2004)
2003
79 Jean-François Boulicaut, Saso Dzeroski: Proceedings of the Second International Workshop on Inductive Databases, 22 September, Cavtat-Dubrovnik, Croatia Rudjer Boskovic Institute, Zagreb, Croatia 2003
78EESaso Dzeroski, Ljupco Todorovski, Peter Ljubic: Using Constraints in Discovering Dynamics. Discovery Science 2003: 297-305
77EESaso Dzeroski, Ljupco Todorovski, Boris Zmazek, Janja Vaupotic, Ivan Kobal: Modelling Soil Radon Concentration for Earthquake Prediction. Discovery Science 2003: 87-99
76EELjupco Todorovski, Saso Dzeroski: Using Domain Specific Knowledge for Automated Modeling. IDA 2003: 48-59
75 Saso Dzeroski, Ljupco Todorovski, Peter Ljubic: Inductive Databases of Polynomial Equations. KDID 2003: 28-43
74 Ljupco Todorovski, Saso Dzeroski: Combining Classifiers with Meta Decision Trees. Machine Learning 50(3): 223-249 (2003)
73EESaso Dzeroski: Multi-relational data mining: an introduction. SIGKDD Explorations 5(1): 1-16 (2003)
72EESaso Dzeroski, Luc De Raedt: Multi-relational data mining: the current frontiers. SIGKDD Explorations 5(1): 100-101 (2003)
71EESaso Dzeroski, Luc De Raedt, Stefan Wrobel: Multirelational data mining 2003: workshop report. SIGKDD Explorations 5(2): 200-202 (2003)
2002
70EESaso Dzeroski: Relational Reinforcement Learning for Agents in Worlds with Objects. Adaptive Agents and Multi-Agents Systems 2002: 306-322
69EELjupco Todorovski, Hendrik Blockeel, Saso Dzeroski: Ranking with Predictive Clustering Trees. ECML 2002: 444-455
68EEBernard Zenko, Saso Dzeroski: Stacking with an Extended Set of Meta-level Attributes and MLR. ECML 2002: 493-504
67 Kurt Driessens, Saso Dzeroski: Integrating Experimentation and Guidance in Relational Reinforcement Learning. ICML 2002: 115-122
66 Saso Dzeroski, Bernard Zenko: Is Combining Classifiers Better than Selecting the Best One. ICML 2002: 123-130
65 Pat Langley, Javier Nicolás Sánchez, Ljupco Todorovski, Saso Dzeroski: Inducing Process Models from Continuous Data. ICML 2002: 347-354
64EESaso Dzeroski: Learning in Rich Representations: Inductive Logic Programming and Computational Scientific Discovery. ILP 2002: 346-349
63EESaso Dzeroski, Bernard Zenko: Stacking with Multi-response Model Trees. Multiple Classifier Systems 2002: 201-211
62EESaso Dzeroski, Luc De Raedt: Multi-Relational Data Mining: a Workshop Report. SIGKDD Explorations 4(2): 122-124 (2002)
2001
61EELjupco Todorovski, Saso Dzeroski: Theory Revision in Equation Discovery. Discovery Science 2001: 389-400
60EESaso Dzeroski, Pat Langley: Computational Discovery of Communicable Knowledge: Symposium Report. Discovery Science 2001: 45-49
59EELjupco Todorovski, Saso Dzeroski: Using Domain Knowledge on Population Dynamics Modeling for Equation Discovery. ECML 2001: 478-490
58EEBernard Zenko, Ljupco Todorovski, Saso Dzeroski: A Comparison of Stacking with Meta Decision Trees to Bagging, Boosting, and Stacking with other Methods. ICDM 2001: 669-670
57 Joaquim Comas, Saso Dzeroski, Karina Gibert, Ignasi R.-Roda, Miquel Sànchez-Marrè: Knowledge discovery by means of inductive methods in wastewater treatment plannt data. AI Commun. 14(1): 45-62 (2001)
56 Saso Dzeroski, Luc De Raedt, Kurt Driessens: Relational Reinforcement Learning. Machine Learning 43(1/2): 7-52 (2001)
55 Peter A. Flach, Saso Dzeroski: Editorial: Inductive Logic Programming is Coming of Age. Machine Learning 44(3): 207-209 (2001)
2000
54 James Cussens, Saso Dzeroski: Learning Language in Logic Springer 2000
53 Ljupco Todorovski, Saso Dzeroski, Ashwin Srinivasan, Jonathan Whiteley, David Gavaghan: Discovering the Structure of Partial Differential Equations from Example Behaviour. ICML 2000: 991-998
52EEDimitar Hristovski, Saso Dzeroski, Borut Peterlin, Anamarija Rozic-Hristovski: Supporting Discovery in Medicine by Association Rule Mining of Bibliographic Databases. PKDD 2000: 446-451
51EELjupco Todorovski, Saso Dzeroski: Combining Multiple Models with Meta Decision Trees. PKDD 2000: 54-64
50 Saso Dzeroski, Damjan Demsar, Jasna Grbovic: Predicting Chemical Parameters of River Water Quality from Bioindicator Data. Appl. Intell. 13(1): 7-17 (2000)
49 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
48 Ivan Bratko, Saso Dzeroski: Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27 - 30, 1999 Morgan Kaufmann 1999
47 Saso Dzeroski, Peter A. Flach: Inductive Logic Programming, 9th International Workshop, ILP-99, Bled, Slovenia, June 24-27, 1999, Proceedings Springer 1999
46EEJames Cussens, Saso Dzeroski, Tomaz Erjavec: Morphosyntactic Tagging of Slovene Using Progol. ILP 1999: 68-79
45EESaso Dzeroski, Hendrik Blockeel, Boris Kompare, Stefan Kramer, Bernhard Pfahringer, Wim Van Laer: Experiments in Predicting Biodegradability. ILP 1999: 80-91
44EESaso Dzeroski, James Cussens, Suresh Manandhar: An Introduction to Inductive Logic Programming and Learning Language in Logic. Learning Language in Logic 1999: 3-35
43EESaso Dzeroski, Tomaz Erjavec: Learning to Lemmatise Slovene Words. Learning Language in Logic 1999: 69-88
42 Hendrik Blockeel, Saso Dzeroski, Jasna Grbovic: Simultaneous Prediction of Mulriple Chemical Parameters of River Water Quality with TILDE. PKDD 1999: 32-40
41 Ljupco Todorovski, Saso Dzeroski: Experiments in Meta-level Learning with ILP. PKDD 1999: 98-106
40 Saso Dzeroski, Nada Lavrac: Editorial. Data Min. Knowl. Discov. 3(1): 5-6 (1999)
39 Nada Lavrac, Saso Dzeroski, Masayuki Numao: Inductive Logic Programming for Relational Knowledge Discovery. New Generation Comput. 17(1): 3-23 (1999)
1998
38EESaso Dzeroski, Nico Jacobs, Martín Molina, Carlos Moure: ILP Experiments in Detecting Traffic Problems. ECML 1998: 61-66
37 Saso Dzeroski, Luc De Raedt, Hendrik Blockeel: Relational Reinforcement Learning. ICML 1998: 136-143
36 Saso Dzeroski, Luc De Raedt, Hendrik Blockeel: Relational Reinforcement Learning. ILP 1998: 11-22
35 Suresh Manandhar, Saso Dzeroski, Tomaz Erjavec: Learning Multilingual Morphology with CLOG. ILP 1998: 135-144
34 Saso Dzeroski, Nico Jacobs, Martín Molina, Carlos Moure, Stephen Muggleton, Wim Van Laer: Detecting Traffic Problems with ILP. ILP 1998: 281-290
33EESaso Dzeroski, Steffen Schulze-Kremer, Karsten R. Heidtke, Karsten Siems, Dietrich Wettschereck, Hendrik Blockeel: Diterpene Structure Elucidation from 13CNMR Spectra with Inductive Logic Programming. Applied Artificial Intelligence 12(5): 363-383 (1998)
32 Blaz Zupan, Saso Dzeroski: Acquiring background knowledge for machine learning using function decomposition: a case study in rheumatology. Artificial Intelligence in Medicine 14(1-2): 101-117 (1998)
1997
31 Nada Lavrac, Saso Dzeroski: Inductive Logic Programming, 7th International Workshop, ILP-97, Prague, Czech Republic, September 17-20, 1997, Proceedings Springer 1997
30 Blaz Zupan, Saso Dzeroski: Acquiring and Validating Background Knowledge for Machine Learning Using Function Decomposition. AIME 1997: 86-97
29 Saso Dzeroski, George Potamias, Vassilis Moustakis, Giorgos Charissis: Automated Revision of Expert Rules for Treating Acute Abdominal Pain in Children. AIME 1997: 98-109
28 Ljupco Todorovski, Saso Dzeroski: Declarative Bias in Equation Discovery. ICML 1997: 376-384
27 Yannis Dimopoulos, Saso Dzeroski, Antonis C. Kakas: Integrating Explanatory and Descriptive Learning in ILP. IJCAI (2) 1997: 900-907
26 Saso Dzeroski, Tomaz Erjavec: Induction of Slovene Nominal Paradigms. ILP 1997: 141-148
25EEWim Van Laer, Luc De Raedt, Saso Dzeroski: On Multi-class Problems and Discretization in Inductive Logic Programming. ISMIS 1997: 277-286
1996
24 Dragan Gamberger, Nada Lavrac, Saso Dzeroski: Noise Elimination in Inductive Concept Learning: A Case Study in Medical Diagnosois. ALT 1996: 199-212
23 Saso Dzeroski, Steffen Schulze-Kremer, Karsten R. Heidtke, Karsten Siems, Dietrich Wettschereck: Applying ILP to Diterpene Structure Elucidation from 13C NMR Spectra. Inductive Logic Programming Workshop 1996: 41-54
22 Saso Dzeroski: Inductive Logic Programming and Knowledge Discovery in Databases. Advances in Knowledge Discovery and Data Mining 1996: 117-152
21 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)
20 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
19EESaso Dzeroski, Ljupco Todorovski, Tanja Urbancic: Handling Real Numbers in ILP: A Step Towards Better Behavioural Clones (Extended Abstract). ECML 1995: 283-286
18 Saso Dzeroski: Knowledge Discovery in a Water Quality Database. KDD 1995: 81-86
17 Saso Dzeroski: Learning First-order Clausal Theories in the Presence of Noise. SCAI 1995: 51-60
16 Saso Dzeroski, Ljupco Todorovski: Discovering Dynamics: From Inductive Logic Programming to Machine Discovery. J. Intell. Inf. Syst. 4(1): 89-108 (1995)
15 Ivan Bratko, Saso Dzeroski: Engineering Applications of ILP. New Generation Comput. 13(3&4): 313-333 (1995)
1994
14EESaso Dzeroski, Igor Petrovski: Discovering Dynamics with Genetic Programming. ECML 1994: 347-350
13 Luc De Raedt, Saso Dzeroski: First-Order jk-Clausal Theories are PAC-Learnable. Artif. Intell. 70(1-2): 375-392 (1994)
12 Jörg-Uwe Kietz, Saso Dzeroski: Inductive Logic Programming and Learnability. SIGART Bulletin 5(1): 22-32 (1994)
1993
11EESaso Dzeroski, Stephen Muggleton, Stuart J. Russell: Learnability of Constrained Logic Programs. ECML 1993: 342-347
10 Saso Dzeroski, Ljupco Todorovski: Discovering Dynamics. ICML 1993: 97-103
9 Luc De Raedt, Nada Lavrac, Saso Dzeroski: Multiple Predicate Learning. IJCAI 1993: 1037-1043
8 Saso Dzeroski: Handling Imperfetc Data in Inductive Logic Programming. SCAI 1993: 111-125
7 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)
6EESaso Dzeroski, Nada Lavrac: Inductive Learning in Deductive Databases. IEEE Trans. Knowl. Data Eng. 5(6): 939-949 (1993)
1992
5 Nada Lavrac, Saso Dzeroski: Background Knowledge and Declarative Bias in Inductive Concept Learning. AII 1992: 51-71
4EESaso Dzeroski, Stephen Muggleton, Stuart J. Russell: PAC-Learnability of Determinate Logic Programs. COLT 1992: 128-135
1991
3EENada Lavrac, Saso Dzeroski, Marko Grobelnik: Learning Nonrecursive Definitions of Relations with LINUS. EWSL 1991: 265-281
2 Saso Dzeroski, Nada Lavrac: Learning Relations from Noisy Examples: An Empirical Comparison of LINUS and FOIL. ML 1991: 399-402
1 Nada Lavrac, Saso Dzeroski, Vladimir Pirnat, Viljem Krizman: Learning Rules for Early Diagnosis of Rheumatic Diseases. SCAI 1991: 138-149

Coauthor Index

1Annalisa Appice [107] [110]
2Anneleen Van Assche [87] [98]
3Natasa Atanasova [123]
4Hendrik Blockeel [33] [36] [37] [42] [45] [69] [81] [84] [87] [91] [96] [98] [99] [117]
5Marko Bohanec [106]
6Jean-François Boulicaut [79]
7Ivan Bratko [15] [48]
8Will Bridewell [118]
9Giorgos Charissis [29]
10Amanda Clare [96] [99]
11Joaquim Comas [57]
12James Cussens [44] [46] [54]
13Marko Debeljak [80]
14Damjan Demsar [50]
15Yannis Dimopoulos [27]
16Kurt Driessens [56] [67] [82] [95] [97]
17Tomaz Erjavec [26] [35] [43] [46] [85]
18Peter A. Flach [47] [55]
19Dragan Gamberger [24] [49]
20David Gavaghan [53]
21Karina Gibert [57]
22Valentin Gjorgjioski [100]
23Jasna Grbovic [42] [50]
24Marko Grobelnik [3]
25Karsten R. Heidtke [23] [33]
26Dimitar Hristovski [52] [113]
27Nico Jacobs [34] [38]
28Antonis C. Kakas [27]
29Dimitar Kazakov [21]
30Jörg-Uwe Kietz [12]
31Ivan Kobal [77]
32Dragi Kocev [102] [109] [123]
33Boris Kompare [45] [84]
34Stefan Kramer [45] [84]
35Viljem Krizman [1] [7]
36Svetislav Krstic [123]
37Wim Van Laer [25] [34] [45] [84]
38Pat Langley [60] [65] [114] [118]
39Nada Lavrac [1] [2] [3] [5] [6] [7] [9] [20] [21] [24] [31] [39] [40] [49] [86]
40Peter Ljubic [75] [78] [88] [89] [90]
41Suresh Manandhar [35] [44]
42Taneli Mielikäinen [104]
43Kosta Mitreski [123]
44Martín Molina [34] [38]
45Carlos Moure [34] [38]
46Vassilis Moustakis [29]
47Stephen Muggleton [4] [11] [34]
48Andreja Naumoski [123]
49Masayuki Numao [39]
50Pance Panov [104] [108] [121] [122] [124]
51Aleksandar Peckov [120]
52Borut Peterlin [52] [113]
53Igor Petrovski [14]
54Bernhard Pfahringer [45] [84]
55Vladimir Pirnat [1] [7]
56George Potamias [29]
57Luc De Raedt [9] [13] [25] [36] [37] [56] [62] [71] [72]
58Ignasi Rodríguez-Roda (Ignasi R.-Roda) [57]
59Anamarija Rozic-Hristovski [52]
60Stuart J. Russell [4] [11]
61Javier Nicolás Sánchez [65]
62Miquel Sànchez-Marrè [57]
63Leander Schietgat [99] [117]
64Steffen Schulze-Kremer [23] [33]
65Karsten Siems [23] [33]
66Ivica Slavkov [100]
67Larisa N. Soldatova [121] [124]
68Ashwin Srinivasan [53]
69Janez Stare [113]
70Olga Stepánková [21]
71Daniela Stojanova [106]
72Jan Struyf [93] [94] [96] [99] [100] [102] [105] [109] [111] [115] [117]
73Katerina Taskova [106]
74Ljupco Todorovski [10] [16] [19] [28] [41] [51] [53] [58] [59] [61] [65] [69] [74] [75] [76] [77] [78] [88] [89] [90] [112] [114] [116] [118] [120]
75Tanja Urbancic [19]
76Janja Vaupotic [77]
77Celine Vens [87] [98] [109] [117]
78Irene Weber [21]
79Dietrich Wettschereck [23] [33]
80Jonathan Whiteley [53]
81Stefan Wrobel [71]
82Filip Zelezný [86]
83Bernard Zenko [58] [63] [66] [68] [80] [83] [93] [119] [122]
84Boris Zmazek [77]
85Blaz Zupan [30] [32]
86Darko Zupanic [21]

Colors in the list of coauthors

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