Inductive Logic Programming

Table of Contents

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   Book Overview
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   Chapter 1 Actions, Causation and Logic Programming
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   Chapter 2 Challenges to Machine Learning: Relations Between Reality and Appearance
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   Chapter 3 First-Order Probabilistic Languages: Into the Unknown
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   Chapter 4 Integration of Learning and Reasoning Techniques
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   Chapter 5 Injecting Life with Computers
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   Chapter 6 On the Connection Between the Phase Transition of the Covering Test and the Learning Success Rate
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   Chapter 7 Revising Probabilistic Prolog Programs
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   Chapter 8 Inductive Logic Programming for Gene Regulation Prediction
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    Chapter 9 QG/GA: A Stochastic Search for Progol
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    Chapter 10 Generalized Ordering-Search for Learning Directed Probabilistic Logical Models
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    Chapter 11 ALLPAD: Approximate Learning of Logic Programs with Annotated Disjunctions
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    Chapter 12 Margin-Based First-Order Rule Learning
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    Chapter 13 Extension of the Top-Down Data-Driven Strategy to ILP
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    Chapter 14 Extracting Requirements from Scenarios with ILP
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    Chapter 15 Learning Recursive Patterns for Biomedical Information Extraction
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    Chapter 16 Towards Learning Non-recursive LPADs by Transforming Them into Bayesian Networks
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    Chapter 17 Multi-class Prediction Using Stochastic Logic Programs
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    Chapter 18 Structuring Natural Language Data by Learning Rewriting Rules
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    Chapter 19 An Efficient Algorithm for Computing Kernel Function Defined with Anti-unification
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    Chapter 20 Towards Automating Simulation-Based Design Verification Using ILP
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    Chapter 21 Minimal Distance-Based Generalisation Operators for First-Order Objects
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    Chapter 22 Efficient and Scalable Induction of Logic Programs Using a Deductive Database System
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    Chapter 23 Inductive Mercury Programming
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    Chapter 24 An ILP Refinement Operator for Biological Grammar Learning
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    Chapter 25 Combining Macro-operators with Control Knowledge
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    Chapter 26 Frequent Hypergraph Mining
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    Chapter 27 Induction of Fuzzy and Annotated Logic Programs
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    Chapter 28 Boosting Descriptive ILP for Predictive Learning in Bioinformatics
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    Chapter 29 Relational Sequence Alignments and Logos
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    Chapter 30 On the Missing Link Between Frequent Pattern Discovery and Concept Formation
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    Chapter 31 Learning Modal Theories
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    Chapter 32 A Mining Algorithm Using Property Items Extracted from Sampled Examples
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    Chapter 33 The Complexity of Translating BLPs to RMMs
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    Chapter 34 Inferring Regulatory Networks from Time Series Expression Data and Relational Data Via Inductive Logic Programming
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    Chapter 35 ILP Through Propositionalization and Stochastic k-Term DNF Learning
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    Chapter 36 θ -Subsumption Based on Object Context
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    Chapter 37 Word Sense Disambiguation Using Inductive Logic Programming
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    Chapter 38 ReMauve: A Relational Model Tree Learner
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    Chapter 39 Relational Data Mining Applied to Virtual Engineering of Product Designs