The Design And Implementation Of Library Recommendation System Based On Data Mining

The rapid development of information technology has promoted the transformation of the information management system of all walks of life.Under the background of information technology gradually mature,the library informatization construction level is becoming more and more high,the digital library with its fast literature retrieval and personalized recommendation was welcomed by readers.Quantity expanded rapidly,through the explosive growth of information collection,readers face huge amounts of documents often not convenient to find the needed information,for the traditional library readers,facing serious problems of poor literature retrieval experience.How to build a reasonable literature retrieval service to improve reader literature retrieval experience,has become a hot research topic in the course of the construction of digital library.The recommendation system designed by using information filtering technology,which can provide personalized recommendation service to users and effectively avoid the phenomenon of information overload.With the help of a library recommender systems,readers can be interested in books retrieval,and retrieval process for automatic filter out information,which readers are not interested in,play a role of traditional book retrieval function optimization.The data foundation of information filtering is reader's borrowing history,recommendation system based on the analysis of the library history intelligent,predicts readers' reading preference,and filter the user recommendation information not interested in.In this paper,based ondata mining and information visualization theory,combining with the existing library books retrieval system,design the recommendation system in university library.A college library in the information management system based on the historical records as the data source,and combines the technique of collaborative filtering recommendation algorithm library system,which designs by using the Django framework,using jieba participles,amCharts figure and D3,js visual library book recommendation list,personalized recommendation and give system intelligent functions such as circulation data synchronization.On the basis of in-depth analysis of library book retrieval function library,clear recommendation system design demand,and then to introduce the design of recommender system implementation process in detail,and state the key technology of information visualization application and recommendation algorithm design process.After completing the design of library recommender system,conduct a comprehensive test,verify the recommendation engine,circulation data synchronization,background management,such as front-end display subsystem's function and performance.In this paper,the research significance is embodied in books for the library retrieval which gives certain intelligent analysis capabilities,to enhance the reader's book retrieval experience,rapid access to information,and has a far-reaching influence on the construction of digital library and the quality of the ascension.