Euler/X: A toolkit for logic-based taxonomy integration

Mingmin Chen, Shizhuo Yu, Nico Franz, Shawn Bowers, Bertram Ludäscher

Research output: Contribution to journalConference articlepeer-review


We introduce Euler/X, a toolkit for logic-based taxonomy integration. Given two taxonomies and a set of alignment constraints between them, Euler/X provides tools for detecting, explaining, and reconciling inconsistencies; finding all possible merges between (consistent) taxonomies; and visualizing merge results. Euler/X employs a number of different underlying reasoning systems, including first-order reasoners (Prover9 and Mace4), answer set programming (DLV and Potassco), and RCC reasoners (PyRCC8). We demonstrate the features of Euler/X and provide experimental results showing its feasibility on various synthetic and real-world examples.

ASJC Scopus subject areas

  • Computer Science(all)


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