Performance analysis of machine learning algorithms in resume recommendation systems

This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.

书目详细资料
Main Authors:	Hasan, Ibteaz, Chakraborty, Ratnadeep, Alam, Md. Ashraful
其他作者:	Chakrabarty, Amitabha
格式:	Thesis
语言:	English
出版:	BRAC University 2018
主题:	Resume Machine learning Recruitment Regression
在线阅读:	http://hdl.handle.net/10361/10187

id	10361-10187
record_format	dspace
spelling	10361-101872022-01-26T10:15:52Z Performance analysis of machine learning algorithms in resume recommendation systems Hasan, Ibteaz Chakraborty, Ratnadeep Alam, Md. Ashraful Chakrabarty, Amitabha Department of Computer Science and Engineering, BRAC University Resume Machine learning Recruitment Regression 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). 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. Ibteaz Hasan Ratnadeep Chakraborty Md. Ashraful Alam B. Computer Science and Engineering 2018-05-22T03:29:05Z 2018-05-22T03:29:05Z 2018 2018-04 Thesis ID 14301029 ID 14301075 ID 14301001 http://hdl.handle.net/10361/10187 en BRAC University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 38 pages application/pdf BRAC University
institution	Brac University
collection	Institutional Repository
language	English
topic	Resume Machine learning Recruitment Regression
spellingShingle	Resume Machine learning Recruitment Regression Hasan, Ibteaz Chakraborty, Ratnadeep Alam, Md. Ashraful Performance analysis of machine learning algorithms in resume recommendation systems
description	This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.
author2	Chakrabarty, Amitabha
author_facet	Chakrabarty, Amitabha Hasan, Ibteaz Chakraborty, Ratnadeep Alam, Md. Ashraful
format	Thesis
author	Hasan, Ibteaz Chakraborty, Ratnadeep Alam, Md. Ashraful
author_sort	Hasan, Ibteaz
title	Performance analysis of machine learning algorithms in resume recommendation systems
title_short	Performance analysis of machine learning algorithms in resume recommendation systems
title_full	Performance analysis of machine learning algorithms in resume recommendation systems
title_fullStr	Performance analysis of machine learning algorithms in resume recommendation systems
title_full_unstemmed	Performance analysis of machine learning algorithms in resume recommendation systems
title_sort	performance analysis of machine learning algorithms in resume recommendation systems
publisher	BRAC University
publishDate	2018
url	http://hdl.handle.net/10361/10187
work_keys_str_mv	AT hasanibteaz performanceanalysisofmachinelearningalgorithmsinresumerecommendationsystems AT chakrabortyratnadeep performanceanalysisofmachinelearningalgorithmsinresumerecommendationsystems AT alammdashraful performanceanalysisofmachinelearningalgorithmsinresumerecommendationsystems
_version_	1814308364573736960

Performance analysis of machine learning algorithms in resume recommendation systems

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