Inductive Logic Programming [electronic resource] : 19th International Conference, ILP 2009, Leuven, Belgium, July 2-4, 2010, Revised Papers /
Material type: TextSeries: Lecture Notes in Artificial Intelligence ; 5989Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2010Edition: 1st ed. 2010Description: XII, 257 p. online resourceContent type:- text
- computer
- online resource
- 9783642138409
- 005.131 23
- QA267-268.5
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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