Automatic Employability Test for Factory Workers using Collaborative Filtering

With the quick increase in world-wide population, need of automation is getting increased in every field. Employability tests are often used to check the ability of an experienced or fresher employee to work in a team and also their skill, to know how their actions can impact others. In this context, automated employability test for factory workers will motivate people to stay employable in the labor force of the future and help the organizations to perform recruitment process in an efficient manner. In this paper, we have proposed an automatic employability test platform using Collaborative filtering where similar and best matched activities have been recognized first by the use of item-based-collaborative filtering and then based on the performance of similar activities done by similar subjects, the ranking of employability has been determined for unknown workers using User-basedcollaborative filtering. If the ranking is higher than a previously defined threshold, the subject is said to be appropriate in the scenario and his/her employability is confirmed, but if the ranking is less than the threshold, then the subject is asked to practice more and take the next assessment of employability. To deal with the difference in body structure and habits of doing same action differently at first, we have considered the mean of the rankings of seven different activities and then weighted rank has been calculated to take the inter personal similarity into account. The proposed system is a novel work in this domain and outperforms the other existing works also.