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An Approach to Re-Representation in Relational Learning
Santiago Ontañón, Enric Plaza
11 - 20
10.3233/978-1-61499-320-9-11
Frontiers in Artificial Intelligence and Applications
Volume 256: Artificial Intelligence Research and Development
Abstract

We 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.

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