Aggregating Author Profiles from Multiple Publisher Networks to Build Author Knowledge Graph
Karim Alinani, Guojun Wang, Annadil Alinani, Dua Hussain Narejo, Mumbere Muyisa Forrest · 2018
The use of recommender systems is widespread having roots in numerous fields. The backbone of the advancement in technology is due to the scientific research, hence, leveraging recommender system to enhance the quality of research and ease various stages from literature review to collaboration, is essential and recently in focus of various researchers. To select a strong candidate for potential collaboration, it is essential to evaluate the work put forward by the author, its impact, and the author influence network. In this paper, we propose a recommender system to aggregate author information from various publisher networks and build author knowledge graph, a commutative profile that enlightens all his contributions, impact and collaboration network. It would be useful for a researcher in understanding the author in great detail and evaluate his work for a potential collaboration.