Toward rank disaggregation: An approach based on linear programming and latent variable analysis

Vincent Vigneron 1 Leonardo Tomazeli Duarte 2
1 IBISC - Informatique, Biologie Intégrative et Systèmes Complexes
2 School of Applied Sciences
Abstract : This work presents an unsupervised approach to the problem of rank disaggregation, which can be defined as the task of decomposing a set of rankings provided by different people (or entities). To accomplish this task, we first discuss the problem of rank aggregation and how it can be solved via linear programming. Then, we introduce a disaggregation method based on rank aggregation and inspired by decomposition methods such as principal component analysis (PCA). The results are preliminary but may pave the way for a better understating of relevant features found in applications such as group decision.
Keywords : Condorcet distance Latent variable analysis Linear programming Rank aggregation Rank disaggregation
Document type :
Conference papers
Complete list of metadatas
https://hal.archives-ouvertes.fr/hal-01484255
Contributor : Frédéric Davesne <>
Submitted on : Tuesday, March 7, 2017 - 9:25:17 AM
Last modification on : Monday, October 28, 2019 - 10:50:21 AM

Identifiers

Collections

UNIV-EVRY | IBISC | IBISC-SIBI | UNIV-PARIS-SACLAY

Citation

Vincent Vigneron, Leonardo Tomazeli Duarte. Toward rank disaggregation: An approach based on linear programming and latent variable analysis. 13th International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA 2017), Feb 2017, Grenoble, France. pp.192--200, ⟨10.1007/978-3-319-53547-0_19⟩. ⟨hal-01484255⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Record views

116

Contact

Informations

CCSD