IDEAS home Printed from https://ideas.repec.org/a/aes/dbjour/v6y2016i3p3-10.html
   My bibliography  Save this article

Exploring Data in Human Resources Big Data

Author

Listed:
  • Adela BARA

    (University of Economic Studies, Bucharest, Romania)

  • Iuliana BOTHA

    (University of Economic Studies, Bucharest, Romania)

  • Anda BELCIU

    (University of Economic Studies, Bucharest, Romania)

  • Bogdan NEDELCU

    (University of Economic Studies, Bucharest, Romania)

Abstract

Nowadays, social networks and informatics technologies and infrastructures are constantly developing and affect each other. In this context, the HR recruitment process became complex and many multinational organizations have encountered selection issues. The objective of the paper is to develop a prototype system for assisting the selection of candidates for an intelligent management of human resources. Such a system can be a starting point for the efficient organization of semi-structured and unstructured data on recruitment activities. The article extends the research presented at the 14th International Conference on Informatics in Economy (IE 2015) in the scientific paper "Big Data challenges for human resources management".

Suggested Citation

  • Adela BARA & Iuliana BOTHA & Anda BELCIU & Bogdan NEDELCU, 2016. "Exploring Data in Human Resources Big Data," Database Systems Journal, Academy of Economic Studies - Bucharest, Romania, vol. 6(3), pages 3-10, January.
    • Handle: RePEc:aes:dbjour:v:6:y:2016:i:3:p:3-10
    as

    Download full text from publisher

    File URL: http://www.dbjournal.ro/archive/21/21_1.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ramona BOLOGA & Razvan BOLOGA & Alexandra FLOREA, 2013. "Big Data and Specific Analysis Methods for Insurance Fraud Detection," Database Systems Journal, Academy of Economic Studies - Bucharest, Romania, vol. 4(4), pages 30-39, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Martin Eling & Davide Nuessle & Julian Staubli, 2022. "The impact of artificial intelligence along the insurance value chain and on the insurability of risks," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 47(2), pages 205-241, April.
    2. Martin Eling & Irina Gemmo & Danjela Guxha & Hato Schmeiser, 2024. "Big data, risk classification, and privacy in insurance markets," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 49(1), pages 75-126, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aes:dbjour:v:6:y:2016:i:3:p:3-10. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Adela Bara (email available below). General contact details of provider: https://edirc.repec.org/data/aseeero.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.