Hilltop Based Recommendation in Co-author Networks

The scale of projects and literatures have been continuously expanded and become more complex with the development of scientific research. Scientific cooperation has become an important trend in the scientific research. Analysis of the co-author network is a big data problem. Without enough data mining, the research cooperation will be limited to some same group, named as “small group” in the co-author networks. This situation has led to the researchers’ lack of openness and limited scientific research results. It is important to recommend some potential collaboration from huge amount of literature. We propose a method based on Hilltop algorithm, an algorithm in search engine, to recommend co-authors by link analysis. The candidate set is screening and scored for recommendation. By setting certain rules, the expert set formation of the Hilltop algorithm is added to the screening. And the score is calculated by the durations and times of the collaborations. The co-authors can be extracted and recommended from the big data of the scientific research literatures through the experiments.