A Prediction System by Assigning of Ranking to CV with the Help of Data Mining Process
S. Naga Mallik Raj,Vignan’s Institute of Information Technology, Visakhapatnam, AP, India
S. Neeraja,Department of CSE, Pydah College of Engineering and Technology, Visakhapatnam, AP, India
This will empower an increasingly powerful approach to short rundown submitted hopeful CVs from an expansive number of candidates giving a predictable and reasonable CV positioning arrangement, which can be legitimately supported. Framework will rank the experience and key aptitudes required for specific employment position. Than framework will rank the CV depends on the experience and other key aptitudes which are required for specific occupation profile. This framework will help the HR division to effortlessly waitlist the applicant dependent on the CV positioning strategy. This framework will center in capability and experience as well as spotlights on other significant angles which are required for specific occupation position. This framework will help the human asset office to choose right contender for specific employment profile which thus give master workforce to the association. Hopeful will transfer their very own CV into the framework which will be additionally utilized by the framework to waitlist their CV. This is one that makes the person introduce himself/herself that one wishes to work at. One should have an effective CV that will help oneself in having the better chances of getting hired by the organisation. The CV or the resume that we prepare may not be having the correct format what the organisation will be various methods of CV building a CV. They want the candidates who come for the interviews for that company want the CV to be designed in that intended format itself.
CV, prediction, extraction, clustering, mining
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© 2018 S. Naga Mallik Raj et al. Published by Global Vision Press. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CCBY4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.