Inductive Logic Programming : 16th International Conference, ILP 2006, Santiago de Compostela, Spain, August 24-27, 2006, Revised Selected Papers / edited by Stephen Muggleton, Ramon Otero, Alireza Tamaddoni-Nezhad.

Format:

Book

Contributor:

Muggleton, Stephen, editor.

Otero, Ramon, editor.

Tamaddoni-Nezhad, Alireza, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence ; 4455.

Lecture Notes in Artificial Intelligence ; 4455

Language:

English

Subjects (All):

Software engineering.

Artificial intelligence.

Computer programming.

Logic, Symbolic and mathematical.

Algorithms.

Software Engineering/Programming and Operating Systems.

Artificial Intelligence.

Programming Techniques.

Mathematical Logic and Formal Languages.

Algorithm Analysis and Problem Complexity.

Local Subjects:

Software Engineering/Programming and Operating Systems.

Artificial Intelligence.

Programming Techniques.

Mathematical Logic and Formal Languages.

Algorithm Analysis and Problem Complexity.

Physical Description:

1 online resource (XII, 456 pages).

Edition:

First edition 2007.

Contained In:

Springer eBooks

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2007.

System Details:

text file PDF

Summary:

The inherent dangers of change are often summed up in the misquoted Chinese curse "May you live in interesting times." The submission procedure for the 16th International Conference of Inductive Logic Programming (ILP 2006) was a radical (hopefully interesting but not cursed) departure from previous years. Submissions were requested in two phases. The ?rst phase involved submission of short papers (three pages) which were then presented at the conference and included in a short papers proceedings. In the second phase, reviewers selected papersforlongpapersubmission(15pagesmaximum).Thesewerethenassessed by the same reviewers, who then decided which papers to include in the journal special issue and proceedings. In the ?rst phase there were a record 77 papers, comparedto the usual20 orso long papersofpreviousyears.Eachpaper was- viewed by three reviewers. Out of these, 71 contributors were invited to submit long papers. Out of the long paper submissions, 7 were selected for the - chine Learning Journal special issue and 27 were accepted for the proceedings. In addition, two papers were nominated by Program Committee referees for the applications prize and two for the theory prize. The papers represent the div- sity and vitality in present ILP research including ILP theory, implementations, search and phase transition, distributed and large-scale learning, probabilistic ILP, biological applications, natural language learning and planning and action learning.

Contents:

Invited Papers

Actions, Causation and Logic Programming

Challenges to Machine Learning: Relations Between Reality and Appearance

First-Order Probabilistic Languages: Into the Unknown

Integration of Learning and Reasoning Techniques

Injecting Life with Computers

Special Issue Extended Abstracts

On the Connection Between the Phase Transition of the Covering Test and the Learning Success Rate

Revising Probabilistic Prolog Programs

Inductive Logic Programming for Gene Regulation Prediction

QG/GA: A Stochastic Search for Progol

Generalized Ordering-Search for Learning Directed Probabilistic Logical Models

ALLPAD: Approximate Learning of Logic Programs with Annotated Disjunctions

Margin-Based First-Order Rule Learning

Research Papers

Extension of the Top-Down Data-Driven Strategy to ILP

Extracting Requirements from Scenarios with ILP

Learning Recursive Patterns for Biomedical Information Extraction

Towards Learning Non-recursive LPADs by Transforming Them into Bayesian Networks

Multi-class Prediction Using Stochastic Logic Programs

Structuring Natural Language Data by Learning Rewriting Rules

An Efficient Algorithm for Computing Kernel Function Defined with Anti-unification

Towards Automating Simulation-Based Design Verification Using ILP

Minimal Distance-Based Generalisation Operators for First-Order Objects

Efficient and Scalable Induction of Logic Programs Using a Deductive Database System

Inductive Mercury Programming

An ILP Refinement Operator for Biological Grammar Learning

Combining Macro-operators with Control Knowledge

Frequent Hypergraph Mining

Induction of Fuzzy and Annotated Logic Programs

Boosting Descriptive ILP for Predictive Learning in Bioinformatics

Relational Sequence Alignments and Logos

On the Missing Link Between Frequent Pattern Discovery and Concept Formation

Learning Modal Theories

A Mining Algorithm Using Property Items Extracted from Sampled Examples

The Complexity of Translating BLPs to RMMs

Inferring Regulatory Networks from Time Series Expression Data and Relational Data Via Inductive Logic Programming

ILP Through Propositionalization and Stochastic k-Term DNF Learning

?-Subsumption Based on Object Context

Word Sense Disambiguation Using Inductive Logic Programming

ReMauve: A Relational Model Tree Learner

Relational Data Mining Applied to Virtual Engineering of Product Designs.

Other Format:

Printed edition:

ISBN:

978-3-540-73847-3

9783540738473

Access Restriction:

Restricted for use by site license.