logo ILP2008

Email ilp2008@labe.felk.cvut.cz

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