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    •   BracU IR
    • School of Engineering and Computer Science (SECS)
    • Department of Computer Science and Engineering (CSE)
    • Thesis & Report, BSc (Computer Science and Engineering)
    • View Item
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    Performance analysis of machine learning algorithms in resume recommendation systems

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    14302029,14301075,14301001_CSE.pdf (1.319Mb)
    Date
    2018-04
    Publisher
    BRAC University
    Author
    Hasan, Ibteaz
    Chakraborty, Ratnadeep
    Alam, Md. Ashraful
    Metadata
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    URI
    http://hdl.handle.net/10361/10187
    Abstract
    We present an evaluation of machine learning algorithms on a model prepared by us for improving the recruitment processes of organizations. The recruitment of candidates, being an important process for any organization, entails the hiring of employees that would be best fit for the job and ultimately beneficial for them. We have taken resumes of candidates of an organization and extracted the attributes (namely academics, qualifications, etc. to name a few) and assessed them according to a scale and a corresponding scoring system to train our system so that the candidates with the best scores can be shortlisted. We applied algorithms like decision tree, support vector machine, multi-linear regression and Bayesian ridge regression to train our system. Of all these the best results were given by decision tree and support vector machine regression.
    Keywords
    Resume; Machine learning; Recruitment; Regression
     
    Description
    This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.
     
    Cataloged from PDF version of thesis.
     
    Includes bibliographical references (pages 36-38).
    Department
    Department of Computer Science and Engineering, BRAC University
    Collections
    • Thesis & Report, BSc (Computer Science and Engineering)

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