title: A modified decision tree algorithm based on genetic algorithm for mobile user classification problem.
abstract: In order to offer mobile customers better service, we should classify the mobile user firstly. Aimed at the limitations of previous classification methods, this paper puts forward a modified decision tree algorithm for mobile user classification, which introduced genetic algorithm to optimize the results of the decision tree algorithm. We also take the context information as a classification attributes for the mobile user and we classify the context into public context and private context classes. Then we analyze the processes and operators of the algorithm. At last, we make an experiment on the mobile user with the algorithm, we can classify the mobile user into Basic service user, E-service user, Plus service user, and Total service user classes and we can also get some rules about the mobile user. Compared to C4.5 decision tree algorithm and SVM algorithm, the algorithm we proposed in this paper has higher accuracy and more simplicity.
authors.affiliation: College of Computer Science & Information Engineering, Zhejiang Gongshang University, Hangzhou 310018, China ; Center for Studies of Modern Business, Zhejiang Gongshang University, Hangzhou 310018, China.
authors.forename: Dong-sheng
authors.initials: DS
authors.lastname: Liu
authors.affiliation: College of Computer Science & Information Engineering, Zhejiang Gongshang University, Hangzhou 310018, China.
authors.forename: Shu-jiang
authors.initials: SJ
authors.lastname: Fan
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D040421:Cell Phone; D003195:Computer Communication Networks; D003258:Consumer Behavior; D003661:Decision Support Techniques; D010363:Pattern Recognition, Automated / Q000379:methods; D013685:Telecommunications; D059015:Wireless Technology