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ORCID21st ILP 2011: Windsor Great Park, UK - Late Breaking Papers
- Stephen H. Muggleton, Hiroaki Watanabe:
Latest Advances in Inductive Logic Programming, ILP 2011, Late Breaking Papers, Windsor Great Park, UK, July 31 - August 3, 2011. Imperial College Press / World Scientific 2014, ISBN 978-1-78326-508-4 - Stephen H. Muggleton, Changze Xu:
Can ILP Learn Complete and Correct Game Strategies? 3-10 - Jianmin Ji, Xiaoping Chen:
Induction in Nonmonotonic Causal Theories for a Domestic Service Robot. 11-18 - Anze Vavpetic, Nada Lavrac:
Using Ontologies in Semantic Data Mining with g-SEGS and Aleph. 19-26 - José Carlos Almeida Santos, Manuel Fonseca de Sam Bento Ribeiro:
Improving Search Engine Query Expansion Techniques with ILP. 27-34 - Hiroyuki Nishiyama, Fumio Mizoguchi:
ILP for Cosmetic Product Selection. 35-42 - Andreas Markitanis, Domenico Corapi, Alessandra Russo
, Emil C. Lupu:
Learning User Behaviours in Real Mobile Domains. 43-51 - Mahito Sugiyama, Kentaro Imajo, Keisuke Otaki, Akihiro Yamamoto:
Discovering Ligands for TRP Ion Channels Using Formal Concept Analysis. 53-60 - Beau Piccart, Hendrik Blockeel, Andy Georges, Lieven Eeckhout:
Predictive Learning in Two-Way Datasets. 61-68 - Barthelemy Dworkin, Andrei Doncescu, Jean-Charles Faye, Katsumi Inoue:
Model of Double-Strand Break of DNA in Logic-Based Hypothesis Finding. 69-76 - Fabrizio Riguzzi, Terrance Swift:
The PITA System for Logical-Probabilistic Inference. 79-86 - Waleed Alsanie, James Cussens:
Learning a Generative Failure-Free PRISM Clause. 87-93 - Bogdan Moldovan, Martijn van Otterlo, Luc De Raedt, Plinio Moreno, José Santos-Victor:
Statistical Relational Learning of Object Affordances for Robotic Manipulation. 95-103 - Man Zhu, Zhiqiang Gao:
Learning from Linked Data by Markov Logic. 105-112 - Filip Zelezný:
Satisfiability Machines. 113-120 - Andreas Kirkeby Fidjeland, Wayne Luk, Stephen H. Muggleton:
Customisable Multi-Processor Acceleration of Inductive Logic Programming. 123-141 - Orlando Muñoz Texzocotetla, René MacKinney-Romero:
Multivalue Learning in ILP. 143-150 - Moez Essaidi, Aomar Osmani, Céline Rouveirol:
Learning Dependent-Concepts in ILP: Application to Model-Driven Data Warehouses. 151-172 - Takashi Yamada, Takayoshi Shoudai:
Graph Contraction Pattern Matching for Graphs of Bounded Treewidth. 173-180 - Nicola Di Mauro, Teresa Maria Altomare Basile, Stefano Ferilli, Floriana Esposito:
mLynx: Relational Mutual Information. 181-188 - Ekaterina Komendantskaya:
Machine Learning Coalgebraic Proofs. 191-198 - Francesca A. Lisi, Umberto Straccia:
Can ILP Deal with Incomplete and Vague Structured Knowledge? 199-206 - Niels Pahlavi, Stephen H. Muggleton:
Towards Efficient Higher-Order Logic Learning in a First-Order Datalog Framework. 209-216 - Robert J. Henderson, Stephen H. Muggleton:
Automatic Invention of Functional Abstractions. 217-224 - Yoshihisa Shiina, Hayato Ohwada:
Using Machine-Generated Soft Constraints for Roster Problems. 227-233 - Jan Van Haaren, Guy Van den Broeck:
Relational Learning for Football-Related Predictions. 237-244
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