An experiment on the impact of relation types towards taxonomy alignment problems

This study investigates the impact of five relation types towards taxonomy alignment problems and finds that the presence and prevalence of each relation type have profound impact on the resulting merged solutions. The five relation types used in this study are: equal , include , included-in , overlap , and disjoint . We take a logic-based approach to work with the taxonomy alignment problem, and evaluate (1) the presence of a relation type and (2) the prevalence of a relation type towards the number of possible worlds (merged solutions) produced. We find that equal relation type has a minimal effect on the number of possible worlds, whereas include , included-in , overlap , and disjoint are all significantly impacting the number of possible worlds. We also find that more than one of a relation type from either of the four ( include , included-in , overlap , disjoint ) can substantially increase the number of possible worlds, with overlap and disjoint contributing to a profound exponential growth of that number. This study demonstrates how choices of relation types are important in taxonomy alignment problems, and that aligning taxonomies beyond equivalence is necessary to accurately capture the nuances of real-world taxonomies. • This study is the first to examine different relation types on taxonomy alignments. • This study finds that only using equals for mapping is not enough. • This study demonstrates how combinations of relation types on alignment matters.