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Johannes Fürnkranz: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Johannes Fürnkranz
    More Efficient Windowing. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 1997, pp:509-514 [Conf]
  2. Franz-Günter Winkler, Johannes Fürnkranz
    On Effort in AI Research: A Description Along Two Dimensions. [Citation Graph (0, 0)][DBLP]
    Deep Blue Versus Kasparov: The Significance for Artificial Intelligence, 1997, pp:56-62 [Conf]
  3. Johannes Fürnkranz
    A Pathology of Bottom-Up Hill-Climbing in Inductive Rule Learning. [Citation Graph (0, 0)][DBLP]
    ALT, 2002, pp:263-277 [Conf]
  4. Johannes Fürnkranz
    From Local to Global Patterns: Evaluation Issues in Rule Learning Algorithms. [Citation Graph (0, 0)][DBLP]
    Local Pattern Detection, 2004, pp:20-38 [Conf]
  5. Klaus Brinker, Johannes Fürnkranz, Eyke Hüllermeier
    A Unified Model for Multilabel Classification and Ranking. [Citation Graph (0, 0)][DBLP]
    ECAI, 2006, pp:489-493 [Conf]
  6. Johannes Fürnkranz
    Top-Down Pruning in Relational Learning. [Citation Graph (0, 0)][DBLP]
    ECAI, 1994, pp:453-457 [Conf]
  7. Johannes Fürnkranz, Bernhard Pfahringer, Hermann Kaindl, Stefan Kramer
    Learning to Use Operational Advice. [Citation Graph (0, 0)][DBLP]
    ECAI, 2000, pp:291-295 [Conf]
  8. Robert Trappl, Johannes Fürnkranz, Johann Petrak
    Digging for Peace: Using Machine Learning Methods for Assessing International Conflict Databases. [Citation Graph (0, 0)][DBLP]
    ECAI, 1996, pp:453-457 [Conf]
  9. Johannes Fürnkranz
    Pairwise Classification as an Ensemble Technique. [Citation Graph (0, 0)][DBLP]
    ECML, 2002, pp:97-110 [Conf]
  10. Johannes Fürnkranz
    FOSSIL: A Robust Relational Learner. [Citation Graph (0, 0)][DBLP]
    ECML, 1994, pp:122-137 [Conf]
  11. Johannes Fürnkranz
    A Tight Integration of Pruning and Learning (Extended Abstract). [Citation Graph (0, 0)][DBLP]
    ECML, 1995, pp:291-294 [Conf]
  12. Johannes Fürnkranz, Peter A. Flach
    An Analysis of Stopping and Filtering Criteria for Rule Learning. [Citation Graph (0, 0)][DBLP]
    ECML, 2004, pp:123-133 [Conf]
  13. Johannes Fürnkranz, Eyke Hüllermeier
    Pairwise Preference Learning and Ranking. [Citation Graph (0, 0)][DBLP]
    ECML, 2003, pp:145-156 [Conf]
  14. Hervé Utard, Johannes Fürnkranz
    Link-Local Features for Hypertext Classification. [Citation Graph (0, 0)][DBLP]
    EWMF/KDO, 2005, pp:51-64 [Conf]
  15. Johannes Fürnkranz
    Round Robin Rule Learning. [Citation Graph (0, 0)][DBLP]
    ICML, 2001, pp:146-153 [Conf]
  16. Johannes Fürnkranz, Peter A. Flach
    An Analysis of Rule Evaluation Metrics. [Citation Graph (0, 0)][DBLP]
    ICML, 2003, pp:202-209 [Conf]
  17. Johannes Fürnkranz, Gerhard Widmer
    Incremental Reduced Error Pruning. [Citation Graph (0, 0)][DBLP]
    ICML, 1994, pp:70-77 [Conf]
  18. Eyke Hüllermeier, Johannes Fürnkranz
    Learning Label Preferences: Ranking Error Versus Position Error. [Citation Graph (0, 0)][DBLP]
    IDA, 2005, pp:180-191 [Conf]
  19. Johannes Fürnkranz
    Exploiting Structural Information for Text Classification on the WWW. [Citation Graph (0, 0)][DBLP]
    IDA, 1999, pp:487-498 [Conf]
  20. Petr Savický, Johannes Fürnkranz
    Combining Pairwise Classifiers with Stacking. [Citation Graph (0, 0)][DBLP]
    IDA, 2003, pp:219-229 [Conf]
  21. Alexander K. Seewald, Johannes Fürnkranz
    An Evaluation of Grading Classifiers. [Citation Graph (0, 0)][DBLP]
    IDA, 2001, pp:115-124 [Conf]
  22. Johannes Fürnkranz
    Noise-Tolerant Windowing. [Citation Graph (0, 0)][DBLP]
    IJCAI (2), 1997, pp:852-859 [Conf]
  23. Johannes Fürnkranz
    A Comparison of Pruning Methods for Relational Concept Learning. [Citation Graph (0, 0)][DBLP]
    KDD Workshop, 1994, pp:371-382 [Conf]
  24. Johannes Fürnkranz
    Modeling Rule Precision. [Citation Graph (0, 0)][DBLP]
    LWA, 2004, pp:147-154 [Conf]
  25. Eyke Hüllermeier, Johannes Fürnkranz, Jürgen Beringer
    On Position Error and Label Ranking through Iterated Choice. [Citation Graph (0, 0)][DBLP]
    LWA, 2005, pp:158-163 [Conf]
  26. Frederik Janssen, Johannes Fürnkranz
    On Trading Off Consistency and Coverage in Inductive Rule Learning. [Citation Graph (0, 0)][DBLP]
    LWA, 2006, pp:306-313 [Conf]
  27. Hendrik Blockeel, Johannes Fürnkranz, Alexia Prskawetz, Francesco C. Billari
    Detecting Temporal Change in Event Sequences: An Application to Demographic Data. [Citation Graph (0, 0)][DBLP]
    PKDD, 2001, pp:29-41 [Conf]
  28. Johannes Fürnkranz, Christian Holzbaur, Robert Temel
    User Profiling for the MELVIL Knowledge Retrieval System. [Citation Graph (0, 0)][DBLP]
    Applied Artificial Intelligence, 2002, v:16, n:4, pp:243-281 [Journal]
  29. Johannes Fürnkranz, Bernhard Pfahringer
    Guest Editorial: First-Order Knowledge Discovery in Databases. [Citation Graph (0, 0)][DBLP]
    Applied Artificial Intelligence, 1998, v:12, n:5, pp:345-361 [Journal]
  30. Johannes Fürnkranz, Johann Petrak, Robert Trappl
    Knowledge Discovery in International Conflict Databases. [Citation Graph (0, 0)][DBLP]
    Applied Artificial Intelligence, 1997, v:11, n:2, pp:91-118 [Journal]
  31. Johannes Fürnkranz
    Separate-and-Conquer Rule Learning. [Citation Graph (0, 0)][DBLP]
    Artif. Intell. Rev., 1999, v:13, n:1, pp:3-54 [Journal]
  32. Johannes Fürnkranz
    Integrative Windowing [Citation Graph (0, 0)][DBLP]
    CoRR, 1998, v:0, n:, pp:- [Journal]
  33. Johannes Fürnkranz
    Round robin ensembles. [Citation Graph (0, 0)][DBLP]
    Intell. Data Anal., 2003, v:7, n:5, pp:385-403 [Journal]
  34. Johannes Fürnkranz
    Hyperlink ensembles: a case study in hypertext classification. [Citation Graph (0, 0)][DBLP]
    Information Fusion, 2002, v:3, n:4, pp:299-312 [Journal]
  35. Johannes Fürnkranz
    Integrative Windowing. [Citation Graph (0, 0)][DBLP]
    J. Artif. Intell. Res. (JAIR), 1998, v:8, n:, pp:129-164 [Journal]
  36. Johannes Fürnkranz
    Round Robin Classification. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2002, v:2, n:, pp:721-747 [Journal]
  37. Johannes Fürnkranz, Eyke Hüllermeier
    Preference Learning. [Citation Graph (0, 0)][DBLP]
    KI, 2005, v:19, n:1, pp:60-0 [Journal]
  38. Michael Bowling, Johannes Fürnkranz, Thore Graepel, Ron Musick
    Machine learning and games. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2006, v:63, n:3, pp:211-215 [Journal]
  39. Johannes Fürnkranz
    Pruning Algorithms for Rule Learning. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1997, v:27, n:2, pp:139-172 [Journal]
  40. Johannes Fürnkranz, Peter A. Flach
    ROC 'n' Rule Learning-Towards a Better Understanding of Covering Algorithms. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2005, v:58, n:1, pp:39-77 [Journal]
  41. Sang-Hyeun Park, Johannes Fürnkranz
    Efficient Pairwise Classification. [Citation Graph (0, 0)][DBLP]
    ECML, 2007, pp:658-665 [Conf]
  42. Eyke Hüllermeier, Johannes Fürnkranz
    On Minimizing the Position Error in Label Ranking. [Citation Graph (0, 0)][DBLP]
    ECML, 2007, pp:583-590 [Conf]
  43. Jan-Nikolas Sulzmann, Johannes Fürnkranz, Eyke Hüllermeier
    On Pairwise Naive Bayes Classifiers. [Citation Graph (0, 0)][DBLP]
    ECML, 2007, pp:371-381 [Conf]
  44. Frederik Janssen, Johannes Fürnkranz
    Meta-Learning Rule Learning Heuristics. [Citation Graph (0, 0)][DBLP]
    LWA, 2007, pp:167-174 [Conf]
  45. Eneldo Loza Mencía, Johannes Fürnkranz
    An Evaluation of Efficient Multilabel Classification Algorithms for Large-Scale Problems in the Legal Domain. [Citation Graph (0, 0)][DBLP]
    LWA, 2007, pp:126-132 [Conf]

  46. An Empirical Investigation of the Trade-Off between Consistency and Coverage in Rule Learning Heuristics. [Citation Graph (, )][DBLP]


  47. An Empirical Comparison of Probability Estimation Techniques for Probabilistic Rules. [Citation Graph (, )][DBLP]


  48. On Meta-Learning Rule Learning Heuristics. [Citation Graph (, )][DBLP]


  49. Pairwise learning of multilabel classifications with perceptrons. [Citation Graph (, )][DBLP]


  50. An Exploitative Monte-Carlo Poker Agent. [Citation Graph (, )][DBLP]


  51. A Comparison of Techniques for Selecting and Combining Class Association Rules. [Citation Graph (, )][DBLP]


  52. A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning. [Citation Graph (, )][DBLP]


  53. Efficient Pairwise Multilabel Classification for Large-Scale Problems in the Legal Domain. [Citation Graph (, )][DBLP]


  54. Binary Decomposition Methods for Multipartite Ranking. [Citation Graph (, )][DBLP]


  55. Efficient Decoding of Ternary Error-Correcting Output Codes for Multiclass Classification. [Citation Graph (, )][DBLP]


  56. Handling Unknown and Imprecise Attribute Values in Propositional Rule Learning: A Feature-Based Approach. [Citation Graph (, )][DBLP]


  57. A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning. [Citation Graph (, )][DBLP]


  58. Efficient Multilabel Classification Algorithms for Large-Scale Problems in the Legal Domain. [Citation Graph (, )][DBLP]


  59. Learning to Recognize Missing E-Mail Attachments. [Citation Graph (, )][DBLP]


  60. Label ranking by learning pairwise preferences. [Citation Graph (, )][DBLP]


  61. Searching for Patterns in Political Event Sequences: Experiments with the Keds Database. [Citation Graph (, )][DBLP]


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