Inductive Logic Programming 17th International Conference, ILP 2007, Corvallis, OR, USA, June 19-21, 2007, Revised Selected Papers /

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Blockeel, Hendrik (Editor ), Ramon, Jan (Editor ), Shavlik, Jude (Editor ), Tadepalli, Prasad (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2008.
Edición:1st ed. 2008.
Colección:Lecture Notes in Artificial Intelligence, 4894
Temas:
Artificial intelligence.
Software engineering.
Computer programming.
Machine theory.
Algorithms.
Data mining.
Artificial Intelligence.
Software Engineering.
Programming Techniques.
Formal Languages and Automata Theory.
Data Mining and Knowledge Discovery.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Invited Talks
  • Learning with Kernels and Logical Representations
  • Beyond Prediction: Directions for Probabilistic and Relational Learning
  • Extended Abstracts
  • Learning Probabilistic Logic Models from Probabilistic Examples (Extended Abstract)
  • Learning Directed Probabilistic Logical Models Using Ordering-Search
  • Learning to Assign Degrees of Belief in Relational Domains
  • Bias/Variance Analysis for Relational Domains
  • Full Papers
  • Induction of Optimal Semantic Semi-distances for Clausal Knowledge Bases
  • Clustering Relational Data Based on Randomized Propositionalization
  • Structural Statistical Software Testing with Active Learning in a Graph
  • Learning Declarative Bias
  • ILP :- Just Trie It
  • Learning Relational Options for Inductive Transfer in Relational Reinforcement Learning
  • Empirical Comparison of "Hard" and "Soft" Label Propagation for Relational Classification
  • A Phase Transition-Based Perspective on Multiple Instance Kernels
  • Combining Clauses with Various Precisions and Recalls to Produce Accurate Probabilistic Estimates
  • Applying Inductive Logic Programming to Process Mining
  • A Refinement Operator Based Learning Algorithm for the Description Logic
  • Foundations of Refinement Operators for Description Logics
  • A Relational Hierarchical Model for Decision-Theoretic Assistance
  • Using Bayesian Networks to Direct Stochastic Search in Inductive Logic Programming
  • Revising First-Order Logic Theories from Examples Through Stochastic Local Search
  • Using ILP to Construct Features for Information Extraction from Semi-structured Text
  • Mode-Directed Inverse Entailment for Full Clausal Theories
  • Mining of Frequent Block Preserving Outerplanar Graph Structured Patterns
  • Relational Macros for Transfer in Reinforcement Learning
  • Seeing the Forest Through the Trees
  • Building Relational World Models for Reinforcement Learning
  • An Inductive Learning System for XML Documents.

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