Sugestão de livros baseada em algoritmo híbrido de recomendação e grau de interesse recente

Abstract

With a vast and growing range of books available, choose your next reading can become a complex job amid so many options. In the context of Brazil, where most readers have to choose well which book to buy, due to the low purchasing power of our population, an assertive recommendation has become more valuable. This article presents a book recommendation algorithm based on a hybrid model, which consists of using both techniques related to association rules and techniques that are based on the content of books, aiming to present unknown books that follow the recent interest of the reader. The model managed to reach an accuracy comparable to other models in the RMSE and MAE metrics and delivers recommendations closely related to the last readings of each reader.