9. ILP 1999: Bled, Slovenia

@proceedings{DBLP:conf/ilp/1999,
  editor    = {Saso Dzeroski and
               Peter A. Flach},
  title     = {Inductive Logic Programming, 9th International Workshop, ILP-99,
               Bled, Slovenia, June 24-27, 1999, Proceedings},
  booktitle = {ILP},
  publisher = {Springer},
  series    = {Lecture Notes in Computer Science},
  volume    = {1634},
  year      = {1999},
  isbn      = {3-540-66109-3},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Invited Papers

• Daphne Koller:
  Probabilistic Relational Models. 3-13
  
• Heikki Mannila:
  Inductive Databases (Abstract). 14
  
• J. Ross Quinlan:
  Some Elements of Machine Learning (Extended Abstract). 15-18
  

Contributed Papers

• Liviu Badea, Monica Stanciu:
  Refinement Operators Can Be (Weakly) Perfect. 21-32
  
• Henrik Boström, Lars Asker:
  Combining Divide-and-Conquer and Separate-and-Conquer for Efficient and Effective Rule Induction. 33-43
  
• Ivan Bratko:
  Refining Complete Hypotheses in ILP. 44-55
  
• Kazuya Chiba, Hayato Ohwada, Fumio Mizoguchi:
  Acquiring Graphic Design Knowledge with Nonmonotonic Inductive Learning. 56-67
  
• James Cussens, Saso Dzeroski, Tomaz Erjavec:
  Morphosyntactic Tagging of Slovene Using Progol. 68-79
  
• Saso Dzeroski, Hendrik Blockeel, Boris Kompare, Stefan Kramer, Bernhard Pfahringer, Wim Van Laer:
  Experiments in Predicting Biodegradability. 80-91
  
• Peter A. Flach, Nicolas Lachiche:
  IBC: A First-Order Bayesian Classifier. 92-103
  
• Alan M. Frisch:
  Sorted Downward Refinement: Building Background Knowledge into a Refinement Operator for Inductive Programming. 104-115
  
• José Hernández-Orallo, M. José Ramírez-Quintana:
  A Strong Complete Schmema for Inductive Functional Logic Programming. 116-127
  
• Tamás Horváth, Zoltán Alexin, Tibor Gyimóthy, Stefan Wrobel:
  Application of Different Learning Methods to Hungarian Part-of-Speech Tagging. 128-139
  
• Dimitar Kazakov:
  Combining LAPIS and WordNet for Learning of LR Parsers with Optimal Semantic Constraints. 140-151
  
• Dimitar Kazakov, Suresh Manandhar, Tomaz Erjavec:
  Learning Word Segmentation Rules for Tag Prediction. 152-161
  
• Boonserm Kijsirikul, Sukree Sinthupinyo:
  Approximate ILP Rules by Backpropagation Neural Network: A Result on Thai Character Recognition. 162-173
  
• Nada Lavrac, Peter A. Flach, Blaz Zupan:
  Rule Evaluation Measures: A Unifying View. 174-185
  
• Nikolaj Lindberg, Martin Eineborg:
  Improving Part of Speech Disambiguation Rules by Adding Linguistic Knowledge. 186-197
  
• Eric Martin, Arun Sharma:
  On Sufficient Conditions for Learnability of Logic Programs from Positive Data. 198-209
  
• Herman Midelfart:
  A Bounded Search Space of Clausal Theories. 210-221
  
• Tetsuhiro Miyahara, Takayoshi Shoudai, Tomoyuki Uchida, Tetsuji Kuboyama, Kenichi Takahashi, Hiroaki Ueda:
  Discovering New Knowledge from Graph Data Using Inductive Logic Programming. 222-233
  
• Stephen Muggleton, Michael Bain:
  Analogical Prediction. 234-244
  
• Shan-Hwei Nienhuys-Cheng, Wim Van Laer, Jan Ramon, Luc De Raedt:
  Generalizing Refinement Operators to Learn Prenex Conjunctive Normal Forms. 245-256
  
• Rupert Parson, Khalid Khan, Stephen Muggleton:
  Theory Recovery. 257-267
  
• Jan Ramon, Luc De Raedt:
  Instance Based Function Learning. 268-278
  
• Chiaki Sakama:
  Some Properties of Invers Resolution in Normal Logic Programs. 279-290
  
• Ashwin Srinivasan, Ross D. King, Douglas W. Bristol:
  An Assessment of ILP-Assisted Models for Toxicology and the PTE-3 Experiment. 291-302
  

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