A Matching Approach Based on Term Clusters for eRecruitment

  • Gülşen Bal
  • Aşkın Karakaş
  • Tunga Güngör
  • Fatmagül Süzen
  • Kemal Can KaraEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9728)


As the Internet occupies our daily lives in all aspects, finding jobs/employees online has an important role for job seekers and companies that hire. However, it is difficult for a job applicant to find the best job that matches his/her qualifications and also it is difficult for a company to find the best qualified candidates based on the company’s job advertisement. In this paper, we propose a system that extracts data from free-structured job advertisements in an ontological way in Turkish language. We describe a system that extracts data from resumés and jobs to generate a matching system that provides job applicants with the best jobs to match their qualifications. Moreover, the system also provides companies to find the best fit for their job advertisement.


Cosine Similarity Term Cluster Pattern Rule Free Format Text Domain Consensus 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This study is supported by TÜBİTAK TEYDEB programme with the project number 3130841.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Gülşen Bal
    • 1
  • Aşkın Karakaş
    • 1
  • Tunga Güngör
    • 1
  • Fatmagül Süzen
    • 1
  • Kemal Can Kara
    • 1
    Email author
  1. 1.Computer Engineering DepartmentBoğaziçi UniversityIstanbulTurkey

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