Information Extraction from Hungarian, English and German CVs for a Career Portal

  • Richárd Farkas
  • András Dobó
  • Zoltán Kurai
  • István Miklós
  • Ágoston Nagy
  • Veronika Vincze
  • János Zsibrita
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8891)

Abstract

Recruiting employees is a serious issue for many enterprises. We propose here a procedure to automatically analyse uploaded CVs then prefill the application form which can save a considerable amount of time for applicants thus it increases user satisfaction. For this purpose, we shall introduce a high-recall CV parsing system for Hungarian, English and German. We comparatively evaluate two approaches for providing training data to our machine learning machinery and discuss other experiences gained.

Keywords

CV parsing recruitment process text mining 

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References

  1. 1.
    McCallum, A., Freitag, D., Pereira, F.: Maximum Entropy Markov Models for Information Extraction and Segmentation. In: Proceedings of the 17th International Conference on Machine Learning, pp. 591–598. Morgan Kaufmann Publishers Inc. (2000)Google Scholar
  2. 2.
    Sutton, C., McCallum, A.: An Introduction to Conditional Random Fields. ArXiv e-prints (2010)Google Scholar
  3. 3.
    Szarvas, G.: Feature Engineering for Domain Independent Named Entity Recognition and Biomedical Text Mining Applications. University of Szeged, Szeged (2008)Google Scholar
  4. 4.
    Dobó, A., Csirik, J.: Computing Semantic Similarity Using Large Static Corpora. In: van Emde Boas, P., Groen, F.C.A., Italiano, G.F., Nawrocki, J., Sack, H. (eds.) SOFSEM 2013. LNCS, vol. 7741, pp. 491–502. Springer, Heidelberg (2013)Google Scholar
  5. 5.
    Patil, S., Palshikar, G.K., Srivastava, R., Das, I.: Learning to Rank Resumes. In: Proceedings of FIRE 2012, ISI Kolkata, India (2012)Google Scholar
  6. 6.
    Yi, X., Allan, J., Croft, W.B.: Matching Resumes and Jobs Based on Relevance Models. In: Proceedings of SIGIR 2007, Amsterdam, The Netherlands, pp. 809–810 (2007)Google Scholar
  7. 7.
    Rode, H., Colen, R., Zavrel, J.: Semantic CV Search using Vacancies as Queries. In: Proceedings of the 12th Dutch-Belgian Information Retrieval Workshop, Ghent, Belgium, pp. 87–88 (2012)Google Scholar
  8. 8.
    Bollinger, J., Hardtke, D., Martin, B.: Using social data for resume job matching. In: Proceedings of DUBMMSM 2012, Maui, Hawaii, pp. 27–30 (2012)Google Scholar
  9. 9.
    Faliagka, E., Ramantas, K., Tsakalidis, A., Tzimas, G.: Application of Machine Learning Algorithms to an online Recruitment System. In: Proceedings of ICIW 2012, Stuttgart, Germany, pp. 215–220 (2012)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Richárd Farkas
    • 1
  • András Dobó
    • 3
  • Zoltán Kurai
    • 3
  • István Miklós
    • 1
  • Ágoston Nagy
    • 1
  • Veronika Vincze
    • 2
  • János Zsibrita
    • 3
  1. 1.Institute of InformaticsUniversity of SzegedSzegedHungary
  2. 2.MTA-SZTE Research Group on Artificial IntelligenceSzegedHungary
  3. 3.Nexum Magyarország kft.SzegedHungary

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