An Intelligent System to Generate Possible Job List for Freelancers

Abstract

Managing job is turning into rugged gradually due to the fact of the massive number of online marketplaces as well as freelancers. Moreover, freelancers frequently fall in hesitation about appealing for the job because he/she obtained an enormous volume of irrelevant job posts from the online marketplaces as email notification or in the news feed which eventually raises depression. Therefore, recommending relevant jobs to freelancers to lessen the job finding time has become a highly important issue. In this paper, we propose an intelligent system to assist the freelancers to find out pertinent jobs from numerous freelancing websites with the aid of inspecting their previous work records and analyzing the facts retrieved from job posts using multiple keyword search algorithm. We use the Association rule mining algorithm to generate a list of frequent skill sets used in the preceding works. The system creates a feasible job list considering freelancer's frequent skill sets, client's rating, the minimum budget/ hourly rate, deadline etc. We perform several experiments to prove the effectiveness of the proposed system. The proposed system accelerates the satisfaction of both parties by reducing the job discovering the time for freelancers and providing suitable bidders concerning the job for requesters.