Design of a Recommender System for Job Searching Using Hybrid System
Python - Based RecommenderSystem Application
(Sprache: Englisch)
By and large, searching for work while examining a rundown of enlisting positions on enrollment locales, which truly cost a lot of time and cash is an irritating thing to do Although most of the time those jobs are not always suitable with users, or users...
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By and large, searching for work while examining a rundown of enlisting positions on enrollment locales, which truly cost a lot of time and cash is an irritating thing to do Although most of the time those jobs are not always suitable with users, or users are not satisfy. By doing this, recruiters waste their time by making sure that they are qualify or not. This thesis seeks to address a very important issue on the recruitment process which is about matching jobs seekers with jobs offers. These days, the coordinating procedure between the candidate and the activity offers is one of the serious issue's organizations need to deal with. Short listing candidates and screening resumes are long time-consuming tasks for the company, especially when 80 percent to 90 percent of the resumes received for a role are unquailed. We have designed and proposed a hybrid personalized recommender system used for job seeking and online recruiting websites adapted to the cold start problem using a collaborating predictive algorithm.
Autoren-Porträt von Muhammad Bin Abubakr Joolfoo, Muhammad Khalid Bin Abubakr Joolfoo
Joolfoo, Muhammad Bin AbubakrWe are in the telecommunications fields together with some months of internship experience at different companies. We have observed different difficulties companies come across and try to bring something and our research has also been published on the International Journal of Sciences: Basic and Applied Research (IJSBAR).
Bibliographische Angaben
- Autoren: Muhammad Bin Abubakr Joolfoo , Muhammad Khalid Bin Abubakr Joolfoo
- 2020, 60 Seiten, Maße: 22 cm, Kartoniert (TB), Englisch
- Verlag: LAP Lambert Academic Publishing
- ISBN-10: 620292098X
- ISBN-13: 9786202920988
Sprache:
Englisch
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