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Updated: Jun 22, 2026

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
Published on: February 23, 2019
Ontology quality assurance through analysis of term transformations
Karin Verspoor1, Daniel Dvorkin, K Bretonnel Cohen
1Center for Computational Pharmacology, University of Colorado Denver, Aurora, CO 80045, USA. karin.verspoor@ucdenver.edu
Motivation:
It is important for the quality of biological ontologies that similar concepts be expressed consistently, or univocally. Univocality is relevant for the usability of the ontology for humans, as well as for computational tools that rely on regularity in the structure of terms. However, in practice terms are not always expressed consistently, and we must develop methods for identifying terms that are not univocal so that they can be corrected.
Results:
We developed an automated transformation-based clustering methodology for detecting terms that use different linguistic conventions for expressing similar semantics. These term sets represent occurrences of univocality violations. Our method was able to identify 67 examples of univocality violations in the Gene Ontology.
Availability:
The identified univocality violations are available upon request. We are preparing a release of an open source version of the software to be available at http://bionlp.sourceforge.net.
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