| With the information explosion of the Internet era, a large amounts of repeated and meaningless data is filled in the Internet. Therefore, it is difficult for people to get their wanted information more efficiently. Along with the popularity of mobile Internet, people are far more eager to hold information. Although the search engines can help to gain information, it is lack of personality, and there exists much less efficient data in the searching results. Recommendation system is able to settle the demand of this aspect according to pushing the personalized information, which reduces the difficulties of getting efficient information for users. Thus the research and application in recommendation system is great developed in recent years.Currently, recommendation system has been widely applied in many industries and fields, however, relatively less in intelligent community. Intelligent community is a hot field in recent years, which is supported by the national policy, researched by companies. It is the product of the modern high-tech development, providing people with intelligent, efficient and convenient living environment and lifestyle.This is the paper mainly researching on how the personalized recommendation method applied to intelligent community, and its advantages used to improve user experience of the community residents. After making a research on the related features of intelligent community, the paper presents the personalized recommendation method CTCF based on intelligent community. The method is introduced by the community factors and time function weighting, which efficiently solves the sparse problem of traditional collaborative filtering algorithm, based on this, offers a relatively complete design of the recommendation system overall framework of intelligent community, and implement it. This system is aimed at providing the users with a more personalized, convenient, safe and efficient software service platform of intelligent community. |
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