Hybrid solution for scalable research articles recommendation

In text mining, clustering and classification are the most important techniques to extract information from textual data. These are techniques which allow us to identify similar groups of textual documents or build classification models based on some similarity. This paper presents a hybrid model based on clustering and classification techniques to recommend research articles to researchers. Since the process of literature review is time consuming, our aim is to automate this process and recommend the most relevant research articles based on users' research field preferences.