Bayesian nonparametric Plackett-Luce models for the analysis of preferences for college degree programmes

  title={Bayesian nonparametric Plackett-Luce models for the analysis of preferences for college degree programmes},
  author={Francçois Caron and Yee Whye Teh and Thomas Brendan Murphy},
In this paper we propose a Bayesian nonparametric model for clustering partial ranking data. We start by developing a Bayesian nonparametric extension of the popular Plackett-Luce choice model that can handle an infinite number of choice items. Our framework is based on the theory of random atomic measures, with prior specified by a completely random measure. We characterise the posterior distribution given data, and derive a simple and effective Gibbs sampler for posterior simulation. We then… CONTINUE READING
Highly Cited
This paper has 26 citations. REVIEW CITATIONS


Publications citing this paper.
Showing 1-10 of 15 extracted citations

Bayesian Non-Parametric Clustering of Ranking Data

IEEE Transactions on Pattern Analysis and Machine Intelligence • 2016
View 5 Excerpts
Highly Influenced

A generalized Swendsen-Wang algorithm for Bayesian nonparametric joint segmentation of multiple images

2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) • 2017
View 1 Excerpt


Publications referenced by this paper.
Showing 1-10 of 52 references

Posterior simulation of normalized random measure mixtures

J . Comput . Graph . Statist . • 2011
View 4 Excerpts
Highly Influenced

Association rule analysis of CAO data

P. D. McNicholas
J . Stat . Soc . Inq . Soc . Irel . • 2007
View 3 Excerpts
Highly Influenced

Gibbs sampling methods for Pitman-Yor mixture models

M. D. Statistics. FALL, E. BARAT
Technical Report, • 2012
View 1 Excerpt

Similar Papers

Loading similar papers…