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  5. Preferences in college applications - a nonparametric Bayesian analysis of top-10 rankings
 
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Preferences in college applications - a nonparametric Bayesian analysis of top-10 rankings

File(s)
FileDescriptionSizeFormat
Download ali.pdf74.6 KB
Author(s)
Ali, Alnur 
Murphy, Thomas Brendan 
Meila, Marina 
Chen, Harr 
Uri
http://hdl.handle.net/10197/2832
Date Issued
10 December 2010
Date Available
10T10:19:16Z March 2011
Abstract
Applicants to degree courses in Irish colleges and universities rank up to ten degree courses from a list of over five hundred. These data provide a wealth of information concerning applicant degree choices. A Dirichlet process mixture of generalized Mallows models are used to explore data from a cohort of applicants. We find strong and diverse clusters, which in turn gains us important insights into the workings of the system. No previously tried models or analysis technique are able to model the data with comparable accuracy.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Keywords
  • Rank Data

  • Clustering

Subject – LCSH
Cluster analysis
College applications--Mathematical models
College choice--Mathematical models
Bayesian statistical decision theory
Web versions
http://www.cs.umass.edu/~wallach/workshops/nips2010css/papers/ali.pdf
Language
English
Status of Item
Peer reviewed
Description
NIPS Workshop on Computational Social Science and the Wisdom of Crowds, December 10th 2010, Whistler, Canada
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-sa/1.0/
Owning collection
Mathematics and Statistics Research Collection
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