Suggest Recommendation for Library Users Using Graphs

The aim of this paper is to prove the usefulness of graphs in solving an ever-present problem for library users: finding books they like and they are looking for. Graphs are known as an important tool in solving conditioned optimization problems. We propose a graph-based system of recommendation which can be easy used in a library for assisting and helping users in finding in real time the books they like. The main advantage of the proposed graph-based approach lies in the ease with which new data or even new entities from different sources are added to the graph without disturbing the entire system. The system uses the similarity scores in order to find the similarity between objects and to get the best recommendation for a user’s request. In the end, we will compare the results from used formulas..