Cost-Oriented Candidate Screening Using Machine Learning Algorithms

Shachar Wild, Mark Last

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Choosing the right candidates for any kind of position, whether it is for academic studies or for a professional job, is not an easy task, since each candidate has multiple traits, which may impact her or his success probability in a different way. Furthermore, admitting inappropriate candidates and leaving out the right ones may incur significant costs to the screening organization. Therefore, such a candidate selection process requires a lot of time and resources. In this paper, we treat this task as a cost optimization problem and use machine learning methods to predict the most cost-effective number of candidates to admit, given a ranked list of all candidates and a cost function. This is a general problem, which applies to various domains, such as: job candidate screening, student admission, document retrieval, and diagnostic testing. We conduct comprehensive experiments on two real-world case studies that demonstrate the effectiveness of the proposed method in finding the optimal number of admitted candidates.

Original languageEnglish
Title of host publicationRecent Challenges in Intelligent Information and Database Systems - 14th Asian Conference, ACIIDS 2022, Proceedings
EditorsEdward Szczerbicki, Krystian Wojtkiewicz, Sinh Van Nguyen, Marcin Pietranik, Marek Krótkiewicz
Place of PublicationSingapore
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages14
ISBN (Print)9789811982330
StatePublished - 2022
Event14th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2022 - Ho Chi Minh City, Viet Nam
Duration: 28 Nov 202230 Nov 2022

Publication series

NameCommunications in Computer and Information Science
Volume1716 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937


Conference14th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2022
Country/TerritoryViet Nam
CityHo Chi Minh City


  • Candidate screening
  • Candidate list truncation
  • Prediction models
  • Constrained optimization
  • Asymmetric error costs

ASJC Scopus subject areas

  • Computer Science (all)
  • Mathematics (all)


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