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A Data Mining Approach for Finding Similar Job Positions to Upgrade a Job Position in a System for Evaluating Competencies

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17310%2F20%3AA21027GT" target="_blank" >RIV/61988987:17310/20:A21027GT - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1109/ICCC49264.2020.9257298" target="_blank" >http://dx.doi.org/10.1109/ICCC49264.2020.9257298</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/ICCC49264.2020.9257298" target="_blank" >10.1109/ICCC49264.2020.9257298</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    A Data Mining Approach for Finding Similar Job Positions to Upgrade a Job Position in a System for Evaluating Competencies

  • Original language description

    This article focuses on creating an approach to find similar job positions based on an existing job position in a system for evaluating competencies. The proposed method uses data mining methods to find similar job positions on a job portal based on input data. The input data is the job position title and the list of competencies. The proposed approach then accesses the relevant job positions in a job portal and compares them with the entered inputs. The output of the approach is a list of the most similar job positions in the job portal, including their description. Then HR manager should use this output for completing the assigned job position and its competencies. The proposed approach is then experimentally verified.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the 2020 21st International Carpathian Control Conference, ICCC 2020

  • ISBN

    978-172811951-9

  • ISSN

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

  • Publisher name

    Institute of Electrical and Electronics Engineers Inc.

  • Place of publication

  • Event location

    Virtual conference

  • Event date

    Oct 27, 2020

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article