Ant Colony Optimization to Discover the Concealed Pattern in the Recruitment Process of an Industry
Journal Title: International Journal on Computer Science and Engineering - Year 2010, Vol 2, Issue 4
Abstract
Recruitment of the most appropriate employees and their etention are the immense challenges for the HR department of most of the industries. Every year IT companies recruit fresh raduates through their campus selection programs. Usually ndustries examine the skills of the candidate by conducting tests, group discussion and number of interviews. This process requires enormous amount of effort and investment. During each phase of the recruitment process, candidates are filtered based on some performance criteria. The recruitment process of an industry differs each year based on their requirement raits and the process and criteria changes among the ndustries. This research focuses on investigating the underlying criteria and tries to capitalize on the existing atterns, to minimize the effort made during the recruitment process. Knowledge about the recruitment process was collected from he domain experts and decision trees were constructed with it to identify superior selection criteria. Most of the machine arning algorithms including decision trees have tainted erformance n high dimensional feature space and ubstantiate significant increase in performance with selected features. In this paper, a novel technique based on Ant Colony ptimization is proposed to identify the attributes that impacts the selection process. The proposed ACO technique assigns heuristic formation for the attributes based on the estimated onditional probabilities. Experiments were carried out using the dataset collected from an industry to identify the feature sets that give reater ccuracy. Decision trees constructed using the C4.5 lgorithm with the set of attributes that influence the recruitment process were used to extract feasible rules after making iscussions with the domain experts.
Authors and Affiliations
N. Sivaram , K. Ramar , M. Janaki Meena
Keywords
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