Telecom Package Recommendation Model Study Based On K-nearest Neighbor Algorithm

With the increasing demand of users,increase of users’ needs,the market segmengation of Telecompackages is becoming more and more detailed.The more diverse and diverse the design of package design and the species are more functional.However,other than bring market advantage,the huge amounts of new packages caused huge information management difficulties to telecom operators,and also gives users too many choices to match their needs.To end this,personalized and intelligent package recommendation are especially important and necessary.It is a trend to obtain useful knowledge from the massive amounts of data,dynamically analyze user needs,scientifically establish the recommended model,this is also the inevitable trend of Telecompackages in the market.In this paper,k-nearest neighbor algorithm is used to analyze the theory,and the Telecom package recommendation model is constructed.Firstly,the k-nearest neighbor algorithm is introduced,and the feasibility of the Telecom package recommendation model based on the algorithm is analyzed.Secondly,based on the concept of Telecom munications package,construction of the telecom package feature information,a description of telecommunications users of consumer behavior and Telecommunications package dimensions and indicators,and describes the feature extraction of the user’s consumption behavior and consumption based on historical data.Finally,this paper describes how to establish a recommendation model for Telecom packages.The user similarity and neighbor set calculation and process are analyzed and compared.It fully proves that the application of k-nearest neighbor algorithm in the field of Telecom package recommendation is feasible and effective.It can be used as a scientific and intelligent recommendation method and management tool for the package operation management of Telecom Enterprises.