Discovering Co-author Relationship in Bibliographic Data Using Similarity Measures and Random Walk Model

Abstract

Discovering the research communities to bring techniques to the world is an interesting topic. In this paper we use the DBLP data to investigate the co-author relationship in a real bibliographic network and predict the interactions between co-authors. We analysis the research trend of authors and conferences based on extracted keywords from paper titles. We can understand research fields and change of research trend to find appropriate co-authors and conferences to submit our work. We also find potential co-authors for an existing author in DBLP data by using a variety of similarity measures and a random walk model. It can be useful for building a recommendation system.