Heat Diffusion Based Search for Experts on World Wide Web

Academic institutions, software development companies and enterprises in the real world need expert human resources. These organizations generally take help of search engines like Google. The results of the search are millions of records with noise varying quality. Further browsing is required in order to identity expert people. This causes ambiguity and time consuming. Recently Guan et al. studied a general expert search problem and provided a solution using co-occurrence based diffusion. In this paper we implement a search application which is web based that uses heat difusion technique to identify web resources that contain details about human experts. Ranking is used for presenting results meaningfully. Our prototype application demonstrates the proof of concept. The empirical results are encouraging.