Ranking Based Mining for Expert Human Resources on the World Wide Web

K. Ashesh, G. Vamsi Krishna

Abstract: In all walks of life, human resources play an important role in the success of any organization in the real world. Finding expert human resources is an open problem for enterprises besides retaining good resources to excel in chosen business. Web Search engines like Google can help in finding expert human resources. However, in such case, the results are in millions of records with varying quality and noise. Browsing search results is again time consuming as the identification of suitable resources is deemed to be tedious provided the voluminous search results. Recently Guan et al. presented an approach based on a ranking model which proved to be effective in finding expert human resources with ease. Influenced by this work, in this paper, we implement a prototype application with web interface that uses a ranking technique in order to provide best results that are interested to end user. Our application demonstrates the proof of concept and the empirical results show encouraging results.

Keywords: Heat diffusion, data mining, expert search, ranking and co-occurrence