Research Of Application Of Recommendation System Algorithm In The Students Personalization Course

With the rapid development of Internet, vast information resources on the Web, itbecomes a very urgent problem that how users can quickly locate the information theyare interested in, the result is the emergence of personalized recommendation.Compared with traditional service, personalized recommendation service can bettermeet the needs of customer, and easier to be accepted by users.Therefore, at present,research of personalized recommendation related technologies has become one ofmore popular and core researches.Through the studies of domestic and foreign research results on personalizedrecommendation in recent years, based on the core issues of personalizedrecommendation, on the basis of the traditional collaborative filtering algorithms andthe AprioriAll algorithm based on association rules, this paper presents a studentsinterest model building which combined of students explicit interest and implicitinterest, Meanwhile, this paper also proposes the implementation of personalizedrecommendation algorithm based on this model. Finally, the evaluations andexperiments are carried out.This paper mainly studied on the following aspects:(1) Proposed the definition of students explicit interest and implicit interest,calculated the weight of explicit interest and implicit interest, and carried out modelbuilding respectively. Using the weighted average method, calculated students interestvalue, built students interest model.(2) Proposed a update model which comply with the laws of natural forgetting.(3)Collaborative filtering recommendation algorithm analysis based on student interest model.(4) Through experiments, the proposed model and algorithm are evaluated andanalyzed. The result showed, in a certain range of data, that the model based on studentinterest and recommendation algorithm which proposed by this paper, improved theaccuracy of recommendation.