Design And Implementation Of Campus News Recommendation System Based On Clustering Algorithm In Jilin University

In recent years,the era of the hot spot is the advent of the era of mobile Internet,the Internet is the wave swept through every field in modern society.With the popularity of mobile communication tools and the development of Internet information technology,the phenomenon of "information overload" has become the inevitable focal point question.Both for the publisher of information,or for the recipient of information,are faced with the challenge of "information overload".Especially for information of the receiver,how to get their needs quickly and valuable information.Thus,personalized information recommendation has become a hot research field.Campus informationization as an important field of social informatization,is faced with the problem.Nowadays comtemporary university studens have much more methods to acquire information,while lacking efficiency,accurateness and intelligence.Around the above background,this paper focus on the construction of campus informatization,how to design and realize mobile campus news recommendation system has carried on the research and practice.The main content of this paper is as follows:This paper studied the personalized recommendation system and the research status and development of news recommendation systems,which led to the future development direction of personalized recommendation will be recommended method combine the advantages of the recommended method combination.Personalized recommendation of the existing methods such as recommendation based on association rules,based on content recommendation,collaborative filtering recommendation are studied,such as analysis of technical principle,application fields and their respective advantages and disadvantages.Combining with the analysis of existing recommendations,this paper proposes a first based on text clustering,and then combines content recommendation and collaborative filtering recommendation method.So this article USES the K-means algorithm for news using keywords characteristics of news text clustering;Focusing on the text similarity for at the same time,the combination of user behavior analysis of the collaborative filtering recommendation.Based on the recommended scheme is put forward in this paper,based on the Android platform was designed and implemented a campus information recommendationsystem,gives the clustering and recommendation technology in the application of the system,the realization of news gathering,the construction of the server,the database and the realization of the Android client and associated test verification.