Design And Implementation Of Book Recommendation System Based On Knowledge Graph

The traditional book recommendation system only pays attention to the user's preferences and does not pay attention to the balance of the user's books.Moreover,the traditional recommendation algorithm ignores the potential relationship between books and books,leading to the irrationality of the recommended book list.The technology improves the book recommendation system and recommends books to users' satisfaction.The book recommendation system analyzes the distance relationship between books and books,and the similarity between users,and the complementarity of the recommended book category to the current user,and develops the book recommendation system.The book recommendation system is mainly divided into algorithm model layers,There are three parts of the system's Web and system server.The algorithm model layer mainly uses the knowledge graph to build the relationship between books and books.The knowledge map between the books is used to obtain the similarity distance and category similarity between books.Based on the user-based filtering recommendation algorithm,the user's rating information for books is supplemented,and the user's rating information for unknown books is supplemented.The iterative processing of the similarity of the book category and the user rating data through the FFM model is used to analyze the user-user relationship.The relationship between books and books is used to further analyze the comprehensive weight of the recommended book list to obtain a recommended book list for users.The web end of the system mainly shows users highly popular books,strongly recommended books,and complementary books.The system server mainly provides functions such as book management,user management,and recording of user reading and browsing behaviors.Extensible interfaces are reserved in the code to facilitate future expansion.The book recommendation system not only solves the user's problem of searching for books,but also recommends books to users in three ways,which not only saves users time to search for books,reads satisfactory books,and secondly,recommends complementary books to users,allowing Users can not only read favorite books,but also supplement their knowledge with complementary books.