Research And Implementation Of Personalized Book Recommendation Technology In University Library Based On User Interest Change

With progress of the time and the rapid development science and technology,people's lives have undergone tremendous changes by the emergence and popularization of the Internet.It can be said that the Internet has long been infiltrated into all walks of life today.However,with the continuous development of technology,the amount of information and data in network is also in constant growth,it is difficult to timely and accurate in the huge database to select the resources which are suit for people or people like when people obtain their information what they need,resulting the efficiency of use of information reduced greatly.Currently,we live in such an "information overload" era.Today,teachers and students have brought a wealth of knowledge with electronic and library resources increasing.Teachers and students have been brought a huge challenge by the increasing electronic and library resources.It is a challenging task to quickly pick out your interest or suit your own resources in a large collection of books.The traditional university library management system can only solve the problem to a certain extent,can provide users with search,query,borrow,return books and other functions.But with development of social and information progress,the preferences of reading of teachers and students are constantly changing,reading becoming more and more widely,reading requirement may gradually show a personalized trend.In order to improve the utilization rate of library resources in colleges and universities,to meet the individual needs of users,we can take the initiative to recommend books for the users,this article studies the personalized recommendation books and users' interests changes,and realize the personalized book recommendation system in university library based on user interest changes.This article is to help teachers and students to solve the problem that people do not know how to pick resources in the massive books,and take the initiative to recommend personalized books for them.This paper is on the basis of analysis of the traditional collaborative filtering recommendation algorithm,considering the user interest change,and analyze that user interest change affect the collaborative filtering recommendation mainly in two core processes,namely,the process of finding similar neighbor sets and the process of forecasting scoring.In this two core process,we introduce regulatory factor which combine time weight and frequency weight together to improve the algorithm.This article presents that the regulatory factor conforms to the Ebbinghaus forgetting principle,which can improve the accuracy of book recommendation.The personalized library recommendation system of the university library is based on the individual recommendation.Firstly,it conducts a demand analysis,including the user demand analysis,the system functional and the system nonfunctional demand.Then,to summarizes and designs the functional structure and database of the system,and the use of the regulatory factor of collaborative filtering recommendation algorithm to achieve personalized book recommendation module,finally,this personalized book recommendation system can be achieved by adopting the java programming language,Browser/Server,SSH framework.The test results show that this system can be more accurate to provide users with books recommended,to improve the library resource utilization.