Inductive Logic Programming [electronic resource] : 19th International Conference, ILP 2009, Leuven, Belgium, July 02-04, 2009. Revised Papers / edited by Luc Raedt.

Contributor(s): Raedt, Luc [editor.] | SpringerLink (Online service)Material type: TextTextSeries: Lecture Notes in Computer Science ; 5989Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2010Description: XII, 257p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783642138409Subject(s): Computer science | Computer software | Logic design | Database management | Data mining | Information storage and retrieval systems | Computer Science | Mathematical Logic and Formal Languages | Database Management | Information Storage and Retrieval | Algorithm Analysis and Problem Complexity | Data Mining and Knowledge Discovery | Logics and Meanings of ProgramsAdditional physical formats: Printed edition:: No titleDDC classification: 005.131 LOC classification: QA8.9-QA10.3Online resources: Click here to access online
Contents:
Knowledge-Directed Theory Revision -- Towards Clausal Discovery for Stream Mining -- On the Relationship between Logical Bayesian Networks and Probabilistic Logic Programming Based on the Distribution Semantics -- Induction of Relational Algebra Expressions -- A Logic-Based Approach to Relation Extraction from Texts -- Discovering Rules by Meta-level Abduction -- Inductive Generalization of Analytically Learned Goal Hierarchies -- Ideal Downward Refinement in the Description Logic -- Nonmonotonic Onto-Relational Learning -- CP-Logic Theory Inference with Contextual Variable Elimination and Comparison to BDD Based Inference Methods -- Speeding Up Inference in Statistical Relational Learning by Clustering Similar Query Literals -- Chess Revision: Acquiring the Rules of Chess Variants through FOL Theory Revision from Examples -- ProGolem: A System Based on Relative Minimal Generalisation -- An Inductive Logic Programming Approach to Validate Hexose Binding Biochemical Knowledge -- Boosting First-Order Clauses for Large, Skewed Data Sets -- Incorporating Linguistic Expertise Using ILP for Named Entity Recognition in Data Hungry Indian Languages -- Transfer Learning via Relational Templates -- Automatic Revision of Metabolic Networks through Logical Analysis of Experimental Data -- Finding Relational Associations in HIV Resistance Mutation Data -- ILP, the Blind, and the Elephant: Euclidean Embedding of Co-proven Queries -- Parameter Screening and Optimisation for ILP Using Designed Experiments -- Don’t Fear Optimality: Sampling for Probabilistic-Logic Sequence Models -- Policy Transfer via Markov Logic Networks -- Can ILP Be Applied to Large Datasets?.
In: Springer eBooks
Item type: E-BOOKS
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Knowledge-Directed Theory Revision -- Towards Clausal Discovery for Stream Mining -- On the Relationship between Logical Bayesian Networks and Probabilistic Logic Programming Based on the Distribution Semantics -- Induction of Relational Algebra Expressions -- A Logic-Based Approach to Relation Extraction from Texts -- Discovering Rules by Meta-level Abduction -- Inductive Generalization of Analytically Learned Goal Hierarchies -- Ideal Downward Refinement in the Description Logic -- Nonmonotonic Onto-Relational Learning -- CP-Logic Theory Inference with Contextual Variable Elimination and Comparison to BDD Based Inference Methods -- Speeding Up Inference in Statistical Relational Learning by Clustering Similar Query Literals -- Chess Revision: Acquiring the Rules of Chess Variants through FOL Theory Revision from Examples -- ProGolem: A System Based on Relative Minimal Generalisation -- An Inductive Logic Programming Approach to Validate Hexose Binding Biochemical Knowledge -- Boosting First-Order Clauses for Large, Skewed Data Sets -- Incorporating Linguistic Expertise Using ILP for Named Entity Recognition in Data Hungry Indian Languages -- Transfer Learning via Relational Templates -- Automatic Revision of Metabolic Networks through Logical Analysis of Experimental Data -- Finding Relational Associations in HIV Resistance Mutation Data -- ILP, the Blind, and the Elephant: Euclidean Embedding of Co-proven Queries -- Parameter Screening and Optimisation for ILP Using Designed Experiments -- Don’t Fear Optimality: Sampling for Probabilistic-Logic Sequence Models -- Policy Transfer via Markov Logic Networks -- Can ILP Be Applied to Large Datasets?.

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