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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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    Incremental learning based intelligent job search system

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    Thesis.pdf (1.261Mb)
    Date
    2015
    Publisher
    BRAC University
    Author
    Afrin, Fahmida
    Nahar, Irin
    Metadata
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    URI
    http://hdl.handle.net/10361/4177
    Abstract
    In today’s world of smart phones and smart machines, our job search systems are still not smart enough. With the increasing population, and the rapid growth of internet usage, online job search is not a new issue anymore. From our very own bdjobs.com to the recent loosemonkies.com, there are many online based job sites. The sites still rely on the Boolean matching, whereas they have large amount of data of job seekers and recruiters. Our goal is to use this CV, Job and recruitment information to train the job search system incrementally, exactly the way, human beings learn. With every successful recruitment, and with every failed approach, the job search system will learn to predict, learn to behave how a recruiter does while recruiting an employee. Thus, not only the job seekers, the recruiters can rely on the job search system too for the best selection of employees.
    Keywords
    Computer science and engineering
    Description
    This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2015.
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    • Thesis & Report, BSc (Computer Science and Engineering)

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