Preliminary information on the conference organization
- SCHEDULE: ILP 2008 will start early morning on September 10 and conclude around 16:00 on September 12. Time alloted for the oral presentations will be 25 minutes including questions for the long papers (main conference track), and 5 minutes for the short papers (late breaking papers track).
- EQUIPMENT: A notebook and a data projector will be available for the presentation. The short papers will also be presented and discussed during special poster sessions. The area for each poster will be 120cm (width) X 150cm (height), that is, slightly larger than the A0 standard.
Main Track
- Using the Bottom Clause and Mode Declarations on FOL Theory Revision from Examples
Ana Luísa Duboc, Aline Paes, Gerson Zaverucha - Logical Hierarchical Hidden Markov Models
Sriraam Natarajan, Hung Bui, Prasad Tadepalli, Kristian Kersting, Weng-Keen Wong - Learning Block-Preserving Outerplanar Graph Patterns and its Application to Data Mining
Hitoshi Yamasaki, Yosuke Sasaki, Takayoshi Shoudai, Tomoyuki Uchida, Yusuke Suzuki - Brave Induction
Chiaki Sakama, Katsumi Inoue - Challenges in Relational Learning for Real Time Systems Applications
Mark Bartlett, Iain Bate, Dimitar Kazakov - A Model to Study Phase Transition and Plateaus in Relational Learning
Erick Alphonse, Aomar Osmani - Discriminative Structure Learning of Markov Logic Networks
Marenglen Biba, Stefano Ferilli, Floriana Esposito - A note on refinement operators for IE-based ILP systems
Alireza Tamaddoni-Nezhad, Stephen Muggleton - Feature Discovery with Type Extension Trees
Manfred Jaeger, Paolo Frasconi, Andrea Passerini - Top-down Induction of Relational Model Trees in Multi-Instance Learning
Annalisa Appice, Michelangelo Ceci, Donato Malerba - A Comparison Between two Statistical Relational Models
Lorenza Saitta, Christel Vrain - An experiment in robot discovery with ILP
Ivan Bratko, Jure Zabkar, Gregor Leban - Feature Construction using Theory-Guided Sampling and Randomised Search
Sachindra Joshi, Ganesh Ramakrishnan, Ashwin Srinivasan - Learning with Kernels in Description Logics
Fanizzi Nicola, Claudia d'Amato, Floriana Esposito - Foundations of Onto-Relational Learning
Francesca A. Lisi, Floriana Esposito - Querying and Merging Heterogeneous Data by Approximate Joins on Higher-Order Terms
Simon Price, Peter Flach - L-Modified ILP Evaluation Functions for positive-only Biological Grammar Learning
Thierry Mamer, Christopher H Bryant, John McCall - DL-FOIL: Concept Learning in Description Logics
Nicola Fanizzi, Claudia d'Amato, Floriana Esposito - Learning Aggregate Functions with Neural Networks Using a Cascade-Correlation Approach
Werner Uwents, Hendrik Blockeel - A Statistical Approach to Incremental Induction of First-Order Hierarchical Knowledge Bases
David Stracuzzi, Tolga Konik
Late Breaking Papers
- Estimating the Parameters of Probabilistic Databases from Probabilistically Weighted Queries and Proofs [Extended Abstract]
Bernd Gutmann, Angelika Kimmig, Kristian Kersting, Luc De Raedt - Combining answer caching with smartcall optimization in mining frequent DL-safe queries
Joanna Jozefowska, Agnieszka Lawrynowicz, Tomasz Lukaszewski - Network Analysis of the ILPnet2 Co-authorship
Qingyi Gao, Peter Flach - Learning Complex Ontology Alignments -- A Challenge for ILP Research
Heiner Stuckenschmidt, Livia Predoiu, Christian Meilicke - Accelerating frequent subgraph search by detecting low support structures
Petr Buryan - Propositionalizing the EM algorithm by BDDs
Masakazu Ishihata, Yoshitaka Kameya, Taisuke Sato, Shin-ichi Minato - Probabilistic Local Pattern Mining
Angelika Kimmig, Luc De Raedt - HiFi: Tractable Propositionalization through Hierarchical Feature Construction
Ondrej Kuzelka and Filip Zelezny - TopLog: ILP using a logic program declarative bias
Stephen Muggleton, Jose Santos, Alireza Tamaddoni-Nezhad - A Simple Model for Sequences of Relational State Descriptions
ingo Thon, niels Landwehr, luc De Raedt - Learning Comprehensible Relational Features to Distinguish Subfossil Decapod Crustacean Dactyls
Mark Goadrich, Jeffrey Agnew - Using Bio-Pathways in Relational Learning
Matej Holec, Filip Zelezny, Jiri Klema, Jiri Svoboda and Jakub Tolar - Predicting Gene Coexpression from Pathway Relations
Karel Moulik and Filip Zelezny - A Sample Complexity for PILP
Hiroaki Watanabe, Stephen Muggleton - Experiments with Czech Linguistic Data and ILP
Jan Dedek, Alan Eckhardt, Peter Vojtáš - On and Off-Policy Relational Reinforcement Learning
Christophe Rodrigues, Pierre Gérard, Céline Rouveirol - Relational Data Mining In Crisis Management
Martin Večeřa, Luboš Popelínský - Multirelational GUHA Method and Genetic Data
Martin Ralbovský, Alexander Kuzmin, Jan Rauch - The phase transition of the bounded ILP consistency problem
Erick Alphonse - Learning Conceptual Predicates for Teleoreactive Logic Programs
Nan Li, David Stracuzzi, Pat Langley - Inductive Graph Logic Programming: work in progress
Christophe Costa Florencio
