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SOON: Supporting the Evaluation of Researchers’ Profiles

  • Antonia Azzini
  • Andrea Galimberti
  • Stefania MarraraEmail author
  • Eva Ratti
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 877)

Abstract

Find Your Doctor (FYD) is the first Job-placement agency in Italy dedicated to PhDs who are leaving the Academia to continue their professional path in companies and organizations. The mission of FYD is to outline the value of the research background as an asset for the development of companies and society as a whole. For this reason we started a research project aimed at building SOON, Skills Out Of Narrative, a HR supporting tool able to extract from the text provided by a person telling his/her experience a set of well defined skills, both soft and hard, creating a profile. The final aim of the project is to produce a list of candidates ranked on the basis of the degree of similarity of their profile w.r.t. the profile required for a certain job position or activity. This paper describes the full architecture of SOON and the idea at the basis of the FYD mission.

Keywords

Soft skills Text extraction Knowledge management 

References

  1. 1.
    Box, S.: Transferable Skills Training for Researchers Supporting Career Development and Research: Supporting Career Development and Research. OECD Publishing, Paris (2012)Google Scholar
  2. 2.
    Deloitte, C.: Researchers’ report 2014. Monitor human resources policies and practices in research, DG Research and Innovation (2014)Google Scholar
  3. 3.
    Allen, J., van der Velden, R.: The Flexible Professional in the Knowledge Society: New Challenges for Higher Education. Higher Education Dynamics. Springer, Dordrecht (2011).  https://doi.org/10.1007/978-94-007-1353-6CrossRefGoogle Scholar
  4. 4.
    Singh, A., Rose, C., Visweswariah, K., Chenthamarakshan, V., Kambhatla, N.: PROSPECT: a system for screening candidates for recruitment. In: Proceedings of the 19th ACM International Conference on Information and Knowledge Management, pp. 659–668. ACM (2010)Google Scholar
  5. 5.
    Poch, M., Bel, N., Espeja, S., Navıo, F.: Ranking job offers for candidates: learning hidden knowledge from big data. In: Language Resources and Evaluation Conference (2014)Google Scholar
  6. 6.
    Kessler, R., Torres-Moreno, J.M., El-Bèze, M.: E-Gen: automatic job offer processing system for human resources. In: Gelbukh, A., Kuri Morales, Á.F. (eds.) MICAI 2007. LNCS (LNAI), vol. 4827, pp. 985–995. Springer, Heidelberg (2007).  https://doi.org/10.1007/978-3-540-76631-5_94CrossRefGoogle Scholar
  7. 7.
    Koperwas, J., Skonieczny, Ł., Kozłowski, M., Andruszkiewicz, P., Rybiński, H., Struk, W.: Intelligent information processing for building university knowledge base. J. Intell. Inf. Syst. 48, 1–23 (2016)Google Scholar
  8. 8.
    Andrews, S., Gibson, H., Domdouzis, K., Akhgar, B.: Creating corroborated crisis reports from social media data through formal concept analysis. J. Intell. Inf. Syst. 47(2), 287–312 (2016)CrossRefGoogle Scholar
  9. 9.
    Jindal, N., Liu, B.: Opinion spam and analysis. In: Proceedings of the 2008 International Conference on Web Search and Data Mining, pp. 219–230. ACM (2008)Google Scholar
  10. 10.
    Bifet, A., Frank, E.: Sentiment knowledge discovery in Twitter streaming data. In: Pfahringer, B., Holmes, G., Hoffmann, A. (eds.) DS 2010. LNCS (LNAI), vol. 6332, pp. 1–15. Springer, Heidelberg (2010).  https://doi.org/10.1007/978-3-642-16184-1_1CrossRefGoogle Scholar
  11. 11.
    Heckman, J., Kautz, T.: Hard evidence on soft skills. Labour Econ. 19, 451–464 (2017)CrossRefGoogle Scholar
  12. 12.
    Joseph, D., Ang, S., Chang, R.H.L., Slaughter, S.A.: Practical intelligence in it: assessing soft skills of it professionals. Commun. ACM 53(2), 149–154 (2010)CrossRefGoogle Scholar
  13. 13.
    Merrill, B., West, L.: Using Biographical Methods in Social Research. SAGE Publications, Thousand Oaks (2009)CrossRefGoogle Scholar
  14. 14.
    Blomeke, S., Zlatkin-Troitschanskaia, O., Kuhn, C., Fege, J.: Modeling and Measuring Competencies in Higher Education. Tasks and Challenges. Sense Publisher, Rotterdam (2013)CrossRefGoogle Scholar
  15. 15.
    Charmaz, K.: Constructing Grounded Theory: A Practical Guide Through Qualitative Analysis. Sage, London (2006)Google Scholar
  16. 16.
    Azzini, A., Galimberti, A., Marrara, S., Ratti, E.: A taxonomy of researchers soft skills. Internal Report, ConsorzioC2T (2017)Google Scholar
  17. 17.
    Azzini, A., Galimberti, A., Marrara, S., Ratti, E.: A classifier to identify soft skills in a researcher textual description. In: Proceedings of EvoStar 2018 (2018, to appear)Google Scholar
  18. 18.
    Boselli, R., Cesarini, M., Marrara, S., Mercorio, F., Mezzanzanica, M., Pasi, G., Viviani, M.: WoLMIS: a labor market intelligence system for classifying web job vacancies. J. Intell. Inf. Syst. 50, 1–26 (2017)Google Scholar
  19. 19.
    Nadeau, D., Sekine, S.: A survey of named entity recognition and classification. Lingvist. Investig. 30(1), 3–26 (2007)CrossRefGoogle Scholar
  20. 20.
    Srikanth, M., Srihari, R.: Biterm language models for document retrieval. In: Proceedings of the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 425–426. ACM (2002)Google Scholar
  21. 21.
    Su, J., Xiong, D., Liu, Y., Han, X., Lin, H., Yao, J., Zhang, M.: A context-aware topic model for statistical machine translation. In: ACL, no. 1, pp. 229–238 (2015)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Antonia Azzini
    • 1
  • Andrea Galimberti
    • 2
  • Stefania Marrara
    • 1
    Email author
  • Eva Ratti
    • 1
  1. 1.Consortium for Technology Transfer C2TCarate BrianzaItaly
  2. 2.University of Milano BicoccaMilanItaly

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