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Data Mining and Revenue Management Methodologies In College Admissions.

The article offers an approach to the college admission process by partitioning. The data mining and revenue management phases of partitioning which can be applied to find solutions for both applicants and colleges are explored. Student applications can be processed dynamically and the college can s...

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Published in:Communications of the ACM Vol. 53; no. 4; pp. 128 - 134
Main Authors: REBBAPRAGADA, SURYA, BASU, AMIT, SEMPLE, JOHN
Format: Article
Published: Association for Computing Machinery Apr2010
Subjects:
University & college admission
Data mining
Revenue management
DYNAMO (Computer program language)
Markov spectrum
College applicants
Online Access:View this record in EBSCOhost
Summary:The article offers an approach to the college admission process by partitioning. The data mining and revenue management phases of partitioning which can be applied to find solutions for both applicants and colleges are explored. Student applications can be processed dynamically and the college can select the best candidate at each point throughout admissions. The data-mining techniques of supervised data mining such as decision tree and neural networks, which can be used to classify students based on their predicted freshman grade point average are noted. The dynamic model that was used with Markovian time periods to generate a bid price table is discussed.