The system will help the human resource department to select right candidate for particular job position, which in turn provide expert workforce for the organization. The system can be used in many businesses sector that may require expert candidate. Admin can easily shortlist a candidate based on t
Personality Prediction System Through CV Analysis
The system will help the human resource department to select right candidate for particular job position, which in turn provide expert workforce for the organization. The system can be used in many businesses sector that may require expert candidate. Admin can easily shortlist a candidate based on their online test marks, CV, and select appropriate candidate for the job. A machine learning approach has been used in analysis of data through content and collaborative filtering. This system will reduce workload of the human resource department.
The aim of the Personality Prediction System through CV Analysis is to help Human Resource Department in shortlisting and acquiring personnel efficiently.
The objectives of the system are as follow:
Admin Panel
Candidate Panel
The proposed system can used in many business sectors that may require expert candidate. This system will reduce workload of the human resources. This will enable a more effective way to short list submitted candidate CVs from a large number of applicants providing a consistent and fair CV ranking policy, which can be legally justified.
The system is being developed to help the Human Resource department to select right candidate for particular job profile which in turn provides expert workforce for the organization. The proposed method matches job seekers based on features extracted from CV and test conducted based on the requirements of the employer.
On the proposed system, candidate will register with all his/her details and enter details in the given format of CV on the system. CV will be analyzed by the system using Machine Learning Classification Algorithm to shortlist candidate.
The system consists of three main modules:
Admin Module
Login – The admin needs to login with his/her admin id and password to set the various parameters of the system and access the sub-modules in Module1
Aptitude Questions – The admin can add the aptitude questions of topics of his/her choice with its respective multiple options.
Personality Questions – In this sub-module, the admin can add the entire personality related question to predict the personality of the applicant. It would be based on the Big Five model of Personality. It comprises of five options such as Openness, Conscientiousness, Extroversion, Agreeableness, and Neuroticism
Job Details – Admin or the recruiter can add the requirements or job details on behalf of the company. System would allow the admin to add job details such as qualification, position, experience, salary, etc.
View Candidates – The admin can view all the registered candidates with its details.
View Result – The admin can view the results of the individual candidates which can be easy for the admin to select the desired candidate.
Candidate Module
Registration and CV Creation – To access the below given modules candidate must fill up registration form and create login credentials to gain access to the system. During the registration process the candidate needs to create and submit their CV by filling the CV form.
Login – The candidate needs to enter the valid credentials to access the below sub-modules.
Test – After successful login into the system, the candidate can proceed with the online test based on aptitude and personality.
Apply for Job – The candidate can view the job details and select the appropriate job where in the candidate meets the parameters as specified by the admin/recruiter.
View Results – On successful completion of the test by the candidate, the candidate can view the result that would be displayed in graphical representation.
CV Analysis
Shortlisted CV’s – Here, all the shortlisted CVs of candidates will be displayed. The short-listing of CV’s is performed by system itself.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Graphic Card | Equipment | 1 | 60000 | 60000 |
| Total in (Rs) | 60000 |
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