Research Collaborator Recommendation System based on citations and Influential citations

Recommendation systems are tools that use various factors to suggest items or ideas to users. These systems often rely on networking and filtering, a technique that utilizes algorithms to analyze user reviews and provide personalized recommendations to users with similar preferences. In this work, a recommendation system to assist with the identification of research collaborators based on their areas of interest and published papers has been explored. With the use of the DBLP database, important attributes such as domain, and citation scores are considered to build a research collaboration system. Three different formulae are used to compute research scores (R_Scores) and the scholars are ranked based on these scores and recommendations are made on the basis of the ranks.