Book Reading and Recommendation Application using Python and Dart

Abstract

Recommender System are new generation internet tool that help user in navigating through information on the internet and receive information related to their preferences. Most of these existing systems are user-based ratings where content-based and collaborative based learning methods are used. These systems' irrationality is their rating technique, which counts the users who have already been unsubscribed from the services and no longer rate books. This paper proposed an effective system for recommending books for online users that rated a book using the clustering method and then found a similarity of that book to suggest a new book. Inksavor is an innovative book reading and recommendation app that seamlessly integrates Python and Dart technologies to redefine the reading experience. Users can explore a diverse library, read, and actively engage with literature by writing, annotating, and sharing their thoughts. The app offers a user-friendly writing interface, enabling aspiring authors to effortlessly create and share their literary works. Key Words: Contend Based Filtering, collaborative based filtering, K-Nearest Neighbour Algorithm(KNN), Recommendation system