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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

Author(s)
Ali, Alnur  
Murphy, Thomas Brendan  
Meila, Marina  
Chen, Harr  
Uri
http://hdl.handle.net/10197/2832
Date Issued
2010-12-10
Date Available
2011-03-10T10:19:16Z
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
Subjects

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
Conference Details
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/
File(s)
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Name

ali.pdf

Size

74.6 KB

Format

Adobe PDF

Checksum (MD5)

da0233fd8a0c835d81ff7df143e12a2c

Owning collection
Mathematics and Statistics Research Collection
Mapped collections
Clique Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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