Optimizing Expert Rankings with Multiple Regression Analysis

Abstract

The primary goal of this research is to establish a methodology that gives significant weight to an expert's qualifications and experience in the expertise ranking process. This methodology aims to enhance the effectiveness of expert identification by taking into account an expert's background and credentials, thus yielding more realistic expert rankings. To achieve this, we incorporate the details of an expert's qualifications and experience into the evaluation process by assigning assumed values, which are then integrated with their expertise level. These combined factors are subsequently utilized as inputs for a multiple regression analysis to generate an optimal ranking of experts. By emphasizing the significance of experience and qualifications in the ranking process, we can significantly improve the precision of our expert ranking mechanism. Our approach employs multiple regression analysis to identify the most suitable subject expert for user query transformation.