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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

DyKOSMap: A framework for mapping adaptation between biomedical knowledge organization systems

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Author(s):
Dos Reis, Julio Cesar [1] ; Pruski, Cedric [2] ; Da Silveira, Marcos [2] ; Reynaud-Delaitre, Chantal [3]
Total Authors: 4
Affiliation:
[1] Univ Estadual Campinas, Inst Comp, BR-13083852 Campinas, SP - Brazil
[2] Luxembourg Inst Sci & Technol, L-1855 Luxembourg - Luxembourg
[3] Univ Paris 11, Lab Rech Informat, F-91405 Orsay - France
Total Affiliations: 3
Document type: Journal article
Source: JOURNAL OF BIOMEDICAL INFORMATICS; v. 55, p. 153-173, JUN 2015.
Web of Science Citations: 3
Abstract

Background: Knowledge Organization Systems (KOS) and their associated mappings play a central role in several decision support systems. However, by virtue of knowledge evolution, KOS entities are modified over time, impacting mappings and potentially turning them invalid. This requires semi-automatic methods to maintain such semantic correspondences up-to-date at KOS evolution time. Methods: We define a complete and original framework based on formal heuristics that drives the adaptation of KOS mappings. Our approach takes into account the definition of established mappings, the evolution of KOS and the possible changes that can be applied to mappings. This study experimentally evaluates the proposed heuristics and the entire framework on realistic case studies borrowed from the biomedical domain, using official mappings between several biomedical KOSs. Results: We demonstrate the overall performance of the approach over biomedical datasets of different characteristics and sizes. Our findings reveal the effectiveness in terms of precision, recall and F-measure of the suggested heuristics and methods defining the framework to adapt mappings affected by KOS evolution. The obtained results contribute and improve the quality of mappings over time. Conclusions: The proposed framework can adapt mappings largely automatically, facilitating thus the maintenance task. The implemented algorithms and tools support and minimize the work of users in charge of KOS mapping maintenance. (C) 2015 Elsevier Inc. All rights reserved. (AU)

FAPESP's process: 14/14890-0 - IMEanT: methods for dealing with meanings and intentions on interactive collaborative systems
Grantee:Julio Cesar dos Reis
Support Opportunities: Scholarships in Brazil - Post-Doctoral