Print Email Facebook Twitter Ensemble ranking Title Ensemble ranking: Aggregation of rankings produced by different multi-criteria decision-making methods Author Mohammadi, Majid (TU Delft Information and Communication Technology; Jheronimus Academy of Data Science) Rezaei, J. (TU Delft Transport and Logistics) Date 2020 Abstract One of the essential problems in multi-criteria decision-making (MCDM) is ranking a set of alternatives based on a set of criteria. In this regard, there exist several MCDM methods which rank the alternatives in different ways. As such, it would be worthwhile to try and arrive at a consensus on this important subject. In this paper, a new approach is proposed based on the half-quadratic (HQ) theory. The proposed approach determines an optimal weight for each of the MCDM ranking methods, which are used to compute the aggregated final ranking. The weight of each ranking method is obtained via a minimizer function that is inspired by the HQ theory, which automatically fulfills the basic constraints of weights in MCDM. The proposed framework also provides a consensus index and a trust level for the aggregated ranking. To illustrate the proposed approach, the evaluation and comparison of ontology alignment systems are modeled as an MCDM problem and the proposed framework is applied to the ontology alignment evaluation initiative (OAEI) 2018, for which the ranking of participating systems is of the utmost importance. Subject Ensemble rankingHalf-quadraticMCDMOntology alignment To reference this document use: http://resolver.tudelft.nl/uuid:592fbf1f-5f2a-4437-9bf1-345ba3d7a6ba DOI https://doi.org/10.1016/j.omega.2020.102254 ISSN 0305-0483 Source Omega, 96 Part of collection Institutional Repository Document type journal article Rights © 2020 Majid Mohammadi, J. Rezaei Files PDF 1_s2.0_S0305048319308448_main.pdf 752.53 KB Close viewer /islandora/object/uuid:592fbf1f-5f2a-4437-9bf1-345ba3d7a6ba/datastream/OBJ/view