The document presents a review of document recommendation systems using boosting-based multi-graph classification. It discusses how existing systems have low accuracy when finding related documents. The proposed system aims to have higher accuracy and less time by using boosting-based multi-graph classification to classify documents, identifying common author relations, and recommending the most relevant documents to the user based on their query. It preprocesses documents before classifying them using multiple graphs and article ranking to provide recommendations.