Abstract
stract: In the last years, job recommender systems have become popular since they successfully reduce information overload by generating personalized job recommendation. Currently recommendation Systems are utilized to handle the issue of the overwhelming amount of data or the information in every domain and enables the clients to concentrate on data that is more relevant to their area of interest. One such field where recommender frameworks can play a vital role is to help workers who works on daily wages basis by recommending a job based on their skills and interest. In the current scenario, with an abundance of different industries and fields, a huge number of jobs are available for the skilled and literate professionals. It is not difficult to find suitable jobs for a person after his field has been identified but the main obstacle for achieving this goal is lack of information and awareness. The problem is that there is no such relevant recommendation system available currently so, we proposed the “Job recommendation system for daily paid workers” by analysing the skills of a particular worker and then finding appropriate jobs in his area of interest. To make this system even more robust, a wide variety of factors are taken into consideration while recommending jobs to a worker’s who work on daily wages basis
Published Version
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