Propositionalization of Relational Data

Nada Lavrač, Vid Podpečan and Marko Robnik-Šikonja
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Nada Lavrač: Jožef Stefan Institute, Department of Knowledge Technologies
Vid Podpečan: Jožef Stefan Institute, Department of Knowledge Technologies
Marko Robnik-Šikonja: University of Ljubljana, Faculty of Computer and Information Science

Chapter Chapter 4 in Representation Learning, 2021, pp 83-105 from Springer

Abstract: Abstract Relational learning addresses the task of learning models or patterns from relational data. Complementary to relational learning approaches that learn directly from relational data, developed in the Inductive Logic Programming research community, this chapter addresses the propositionalization approach of first transforming a relational database into a single-table representation, followed by a model or pattern construction step using a standard machine learning algorithm.

Date: 2021
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DOI: 10.1007/978-3-030-68817-2_4

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