Recommending Related Research Papers by Topic Modelling

The modern world generates information at an ever-increasing rate. This information explosion also includes the number of published academic research papers. Researchers have access to a variety of digital libraries to retrieve information. Digital libraries often offer access to a number of journal articles and books. Although digital libraries have search mechanisms, it still takes much time to find related research papers. To ease the process of searching for related research papers, The main objective of this study was to develop a model that uses machine learning techniques to recommend related research papers based on an input research paper. The model is implemented and demonstrated using a prototype. The prototype was used to graphically define a model for the creation of a system to recommend related research papers.