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- W3008560015 abstract "Tailored military recruitment, a strategy that focuses on a subset of population with the highest recruiting potential that corresponds to the specific profile for a military occupation, is being considered by the Canadian Armed Forces. This paper applies unsupervised machine learning to group postal codes into clusters, then rank them using historical application data. The ranking considers both successful and unsuccessful applicants, making it adaptable to specific campaign requirements. Using multiple machine learning methods and combining the resulting scores, a refined set of ranked postal codes is obtained for future recruitment campaigns." @default.
- W3008560015 created "2020-03-06" @default.
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- W3008560015 date "2019-12-01" @default.
- W3008560015 modified "2023-10-16" @default.
- W3008560015 title "Ranking Clusters of Postal Codes to Improve Recruitment in the Canadian Armed Forces" @default.
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- W3008560015 doi "https://doi.org/10.1109/icmla.2019.00197" @default.
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