Inductive Logic Programming : 14th International Conference, ILP 2004, Porto, Portugal, September 6-8, 2004, Proceedings

Rui Camacho

ISBN 10: 3540229418 / ISBN 13: 9783540229414

Edité par Springer Berlin Heidelberg, 2004

A propos de cet article

Druck auf Anfrage Neuware - Printed after ordering - How often we recall, with regret , wrote Mark Twain about editors, that Napoleon once shot at a magazine editor and missed him and killed a publisher. But we remember with charity, that his intentions were good. Fortunately, we live in more forgiving times, and are openly able to express our pleasure at being the editors of this volume containing the papers selected for presentation at the 14th International Conference on Inductive Logic Programming. ILP 2004 was held in Porto from the 6th to the 8th of September, under the auspices of the Department of Electrical Engineering and Computing of the Faculty of Engineering of the University of Porto (FEUP), and the Laborat orio de Intelig encia Arti cial e Ci encias da Computa c ao (LIACC). This annual me- ing of ILP practitioners and curious outsiders is intended to act as the premier forum for presenting the most recent and exciting work in the eld. Six invited talks three from elds outside ILP, but nevertheless highly relevant to it and 20 full presentations formed the nucleus of the conference. It is the full-length papersofthese20presentationsthatcomprisethebulkofthisvolume. Asisnow common with the ILP conference, presentations made to a Work-in-Progress track will, hopefully, be available elsewhere. We gratefully acknowledge the continued support of Kluwer Academic P- lishers for the Best Student Paper award on behalf of the Machine Lea- ing journal; and Springer-Verlag for continuing to publish the proceedings of these conferences.

N° de réf. du vendeur 9783540229414

Détails bibliographiques

• Titre: Inductive Logic Programming : 14th International Conference, ILP 2004, Porto, Portugal, September 6-8, 2004, Proceedings
• Éditeur: Springer Berlin Heidelberg
• Date de parution: 2004
• Langue: anglais
• ISBN à 10 chiffres: 3540229418
• ISBN à 13 chiffres: 9783540229414
• Reliure: Taschenbuch
• État de l'article: Neu
• Dimensions: 235 L x 155 H x 21 P (en millimètres) 235 millimètres de largeur par 155 millimètres de hauteur par 21 millimètres de profondeur
• Poids: 569 grammes

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Synopsis

Invited Papers.- Automated Synthesis of Data Analysis Programs: Learning in Logic.- At the Interface of Inductive Logic Programming and Statistics.- From Promising to Profitable Applications of ILP: A Case Study in Drug Discovery.- Systems Biology: A New Challenge for ILP.- Scaling Up ILP: Experiences with Extracting Relations from Biomedical Text.- Research Papers.- Macro-Operators Revisited in Inductive Logic Programming.- Bottom-Up ILP Using Large Refinement Steps.- On the Effect of Caching in Recursive Theory Learning.- FOIL-D: Efficiently Scaling FOIL for Multi-relational Data Mining of Large Datasets.- Learning an Approximation to Inductive Logic Programming Clause Evaluation.- Learning Ensembles of First-Order Clauses for Recall-Precision Curves: A Case Study in Biomedical Information Extraction.- Automatic Induction of First-Order Logic Descriptors Type Domains from Observations.- On Avoiding Redundancy in Inductive Logic Programming.- Generalization Algorithms for Second-Order Terms.- Circumscription Policies for Induction.- Logical Markov Decision Programs and the Convergence of Logical TD(?).- Learning Goal Hierarchies from Structured Observations and Expert Annotations.- Efficient Evaluation of Candidate Hypotheses in -log.- An Efficient Algorithm for Reducing Clauses Based on Constraint Satisfaction Techniques.- Improving Rule Evaluation Using Multitask Learning.- Learning Logic Programs with Annotated Disjunctions.- A Simulated Annealing Framework for ILP.- Modelling Inhibition in Metabolic Pathways Through Abduction and Induction.- First Order Random Forests with Complex Aggregates.- A Monte Carlo Study of Randomised Restarted Search in ILP.- Addendum.- Learning, Logic, and Probability: A Unified View.