University of Illinois Urbana-Champaign

ADMIT - a web-based system to facilitate graduate admission process

Babichenko, Dmitriy; Druzdzel, Marek

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Babichenko240.epub
Babichenko240.pdf

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https://hdl.handle.net/2142/89301

Description

Title
ADMIT - a web-based system to facilitate graduate admission process
Author(s)
Babichenko, Dmitriy; Druzdzel, Marek
Issue Date
2016-03-15
Keyword(s)
  • graduate admissions
  • Bayesian networks
  • machine learning
Date of Ingest
2016-03-08T22:51:37Z
Abstract
In this paper we describe ADMIT, a software application developed to assist the graduate admissions process at the University of Pittsburgh School of Information Sciences (SIS). ADMIT uses a Bayesian network model built from historical admissions data and academic performance records to predict how likely each applicant is to succeed. The system rank-orders applicants based on the probability of their success in the Master of Science in Information Science (MSIS) program and presents results as an ordered list and as a histogram to the admission committee members. The system also enables users to see a graphical representation of the model (a causal graph) and observe how each input data point affects the system’s suggestions.
Publisher
iSchools
Series/Report Name or Number
IConference 2016 Proceedings
Type of Resource
text
Genre of Resource
Conference Paper / Presentation
Language
eng
Permalink
http://hdl.handle.net/2142/89301
DOI
https://doi.org/10.9776/16240
Copyright and License Information
Copyright 2016 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.

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iConference 2016 Papers PRIMARY