Rank aggregation using latent-scale distance-based models

DOI10.1007/s11222-018-9811-9zbMath1430.62051OpenAlexW2796166171WikidataQ130039259 ScholiaQ130039259MaRDI QIDQ2329771

Philip L. H. Yu, Hang Xu

Publication date: 18 October 2019

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11222-018-9811-9

zbMATH Keywords

mixture modelingranking dataincomplete rankinglatent-scale distance-based modelrank aggregration

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Statistical ranking and selection procedures (62F07)

Related Items (3)

A generalized Mallows model based on \(\phi\)-divergence measures ⋮ Social order statistics models for ranking data with analysis of preferences in social networks ⋮ Asymptotic properties of Lee distance

Uses Software

• PerMallows

Cites Work

• Unnamed Item
• Unnamed Item
• Optimization by Simulated Annealing
• Experiments with Kemeny ranking: What works when?
• Thermodynamical approach to the travelling salesman problem: An efficient simulation algorithm
• Tackling the rank aggregation problem with evolutionary algorithms
• Mixtures of distance-based models for ranking data
• Sampling and learning Mallows and generalized Mallows models under the Cayley distance
• Modern multidimensional scaling. Theory and applications.
• NON-NULL RANKING MODELS. I
• Integration of Ranked Lists via Cross Entropy Monte Carlo with Applications to mRNA and microRNA Studies
• Bayesian Aggregation of Order-Based Rank Data
• Combining Results of Microarray Experiments: A Rank Aggregation Approach

This page was built for publication: Rank aggregation using latent-scale distance-based models