Abstract
As for today’s era, recruitment can be considered as one of most difficult process to undergo for job seeking candidate. Many fresher candidates face issue while job recruitment process to undergo which field of interest. The proposed system will help the user to overcome this difficulties by matching their work experience, skills and other details with appropriate companies suitable for respective user. The system will also help experienced users in getting their intended job on the basis of their last job profile. The job recommendation algorithm developed is tedious nor complicated and will be using user-friendly approach to implement job search.The proposed system consist of user dataset with various attributes and company dataset with company details. The profile matching of user with the respective companies can be done using various recommendation algorithms such as content-based,collaborative and hybrid filtering. Since, the content-based and collaborative approach have their own disadvantages, so here implement hybrid filtering which overcomes the disadvantages of the content-based and collaborative filtering. The user can expect a well-proof recommendation from our model. The Project will focus of developing the job recommendation system using hybrid filtering. As for today’s era, recruitment can be considered as one of most difficult process to undergo for job seeking candidate. Here, our job recommendation system comes in picture which neither is tedious nor complicated and makes use of user-friendly approach and helps user to accomplish the task easily.The project will also be focusing on developing the android application which will add a better user interface. The Android application will be user friendly and the user just have to fill in basic details such as his past years of experiences, project, internship, etc. That’s it,the rest part of recommending the job to the users will be done safely by the recommendation model of this project.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.