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Refinement-based Disintegration: An Approach to Re-representation in Relational Learning

AuthorsOntañón, Santiago; Plaza, Enric
Refinement operators
Relational learning
Issue Date2015
PublisherIOS Press
CitationAI Communications 28: 35- 46 (2015)
AbstractWe present a new approach lo learn from relational data based on re-representation of the examples. This approach, called property-based re-representation is based on a new analysis of the structure of refinement graphs used in ILP and relational learning in general. This analysis allows the characterization of relational examples by a set of multi-relational patterns called properties. Using them, we perform a property-based re-representation of relational examples that facilitates the development of relational learning techniques. Additionally, we show the usefulness of re-representation with a collection of experiments in the context of nearest neighbor classification. © 2015 - IOS Press and the authors.
Identifiersdoi: 10.3233/AIC-140621
issn: 0921-7126
Appears in Collections:(IIIA) Artículos
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