A Reviewer Recommendation System Based on Collaborative Intelligence
Kai-Hsiang Yang, Tai-Liang Kuo, Hahn-Ming Lee, Jan-Ming Ho · 2009
In this paper, expert-finding problem is transformed to a classification issue. We build a knowledge database to represent the expertise characteristic of domain from web information constructed by collaborative intelligence, and an incremental learning method is proposed to update the database. Furthermore, results are ranked by measuring the correlation in the concept network from online encyclopedia. In our experiments, we use the real world dataset which comprise 2,701 experts who are categorized into 8 expertise domains. Our experimental results show that the expertise knowledge extracted from collaborative intelligence can improve efficiency and effect of classification and increase the precision of ranking expert at least 20%.