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An Overview of Knowledge Management Techniques for e-Recruitment

Author

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  • Jorge Martinez-Gil

    (Group of Knowledge Representation & Semantics, Software Competence Center Hagenberg, Softwarepark 21, A-4232 Hagenberg, Austria)

Abstract

The number of potential job candidates and therefore, costs associated with their hiring, has grown significantly in the recent years. This is mainly due to both the complicated situation of the labour market and the increased geographical flexibility of employees. Some initiatives for making the e-Recruitment processes more efficient have notably improved the situation by developing automatic solutions. But there are still some challenges that remain open since traditional solutions do not consider semantic relations properly. This problem can be appropriately addressed by means of a sub discipline of knowledge management called semantic processing. Therefore, we overview the major techniques from this field that can play a key role in the design of a novel business model that is more attractive for job applicants and job providers.

Suggested Citation

  • Jorge Martinez-Gil, 2014. "An Overview of Knowledge Management Techniques for e-Recruitment," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 13(02), pages 1-9.
    • Handle: RePEc:wsi:jikmxx:v:13:y:2014:i:02:n:s0219649214500142
    DOI: 10.1142/S0219649214500142
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    References listed on IDEAS

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    1. J.O. Daramola & O.O. Oladipupo & A.G. Musa, 2010. "A fuzzy expert system (FES) tool for online personnel recruitments," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 6(4), pages 444-462.
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    Cited by:

    1. Jorge Martinez-Gil & Alejandra Lorena Paoletti & Mario Pichler, 0. "A Novel Approach for Learning How to Automatically Match Job Offers and Candidate Profiles," Information Systems Frontiers, Springer, vol. 0, pages 1-10.
    2. Jorge Martinez-Gil & Alejandra Lorena Paoletti & Mario Pichler, 2020. "A Novel Approach for Learning How to Automatically Match Job Offers and Candidate Profiles," Information Systems Frontiers, Springer, vol. 22(6), pages 1265-1274, December.

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