Design And Implementation Of Book Recommendation System Based On Data Mining

The rapid development of information technology has pushed forward the transformation process of information management in all walks of life.With the gradual maturity of information technology,the construction level of library information also becomes higher,and the digital library,quick retrieval of documents,personalized recommendation and other functions are popular with readers.In virtue of the explosive growth of information,the volume of library collections has promptly expanded.When faced with massive volumes of literature,the readers usually can not find their needed information easily.Thus,for traditional library readers,they will face the problem of poor experience in retrieving document.How to construct a reasonable document retrieval service to improve the reader's document retrieval experience has become a hot research topics in the process of digital library construction.The recommendation system designed by using data mining technology can provide personalized recommendation service for users,and can effectively avoid the overload phenomenon of information.With the help of book recommendation system,readers can search books that they are interested in,and it can automatically filter out the information that readers are not interested in during the retrieval process,which plays an important role in the optimization of traditional book retrieval function.The data foundation of data mining is the reader's borrowing history record.The recommendation system can intelligently predict the reader's reading preference and filter the recommendation information that the users are not interested in according to the analysis of the borrowing history record.Based on the deep analysis of the library retrieval function,this paper clarifies the design requirements of the book recommendation system,and then makes detailed introduction on the design and implementation process of this system and demonstrates the application of information visualization technology and the design process of recommendation algorithm.This paper takes the theory of data mining and information visualization as its basic theories and combines with the existing library retrieval system to design the university library recommendation system.This paper takes the book borrowing recording history of a college library management system as its data source and combines with collaborative filtering algorithms to conduct the design of book recommendation system.It adopts Django framework,jieba word segmentation,amCharts and D3.js visualization library to endow the system with the intelligent functions of book recommendation rankings,personalized recommendations and circulation data synchronization and so on.After completing the design of the book recommendation system,it carries out overall test on library recommendation system by Loadrunner to verify the recommendation engine,circulation data synchronization,back-stage management,front-end display and other functions and performances of subsystems.