Comparative evaluation of approaches to propositionalizationMark-A. Krogel, Simon Rawles, Filip Zelezn�, Peter Flach, Nada Lavrač, Stefan Wrobel, Comparative evaluation of approaches to propositionalization. Proceedings of the 13th International Conference on Inductive Logic Programming (ILP'2003). Tamas Horvath, Akihiro Yamamoto, (eds.). ISBN 3-540-20144-0, pp. 194–217. October 2003. PDF, 171 Kbytes.
Propositionalization has already been shown to be a promising approach for robustly and effectively handling relational data sets for knowledge discovery. In this paper, we compare up-to-date methods for propositionalization from two main groups: logic-oriented and database-oriented techniques. Experiments using several learning tasks --- both ILP benchmarks and tasks from recent international data mining competitions --- show that both groups have their specific advantages. While logic-oriented methods can handle complex background knowledge and provide expressive first-order models, database-oriented methods can be more efficient especially on larger data sets. Obtained accuracies vary such that a combination of the features produced by both groups seems a further valuable venture.