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A modified decision tree algorithm based on genetic algorithm for mobile user classification problem.

Liu DS, Fan SJ - ScientificWorldJournal (2014)

Bottom Line: In order to offer mobile customers better service, we should classify the mobile user firstly.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.

View Article: PubMed Central - PubMed

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.

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.

Show MeSH
Processes of algorithm.
© Copyright Policy - open-access
Related In: Results  -  Collection


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fig3: Processes of algorithm.

Mentions: The idea of the algorithm we proposed in this paper is that we firstly use the decision tree algorithm to generate the mobile user classification rules, and then according to the attribute of the rule, such as accuracy, support, simplicity, and gain ratio, we construct the fitness function of genetic algorithm. The larger the value of the fitness is, the more the optimal rule will be. We use the crossover operation and mutation operation of genetic to adjust the fitness function, so the fitness value will reach to the maximum value, and the rule will be optimization. The processes are shown in Figure 3. We will describe these steps in following sections.


A modified decision tree algorithm based on genetic algorithm for mobile user classification problem.

Liu DS, Fan SJ - ScientificWorldJournal (2014)

Processes of algorithm.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3934380&req=5

fig3: Processes of algorithm.
Mentions: The idea of the algorithm we proposed in this paper is that we firstly use the decision tree algorithm to generate the mobile user classification rules, and then according to the attribute of the rule, such as accuracy, support, simplicity, and gain ratio, we construct the fitness function of genetic algorithm. The larger the value of the fitness is, the more the optimal rule will be. We use the crossover operation and mutation operation of genetic to adjust the fitness function, so the fitness value will reach to the maximum value, and the rule will be optimization. The processes are shown in Figure 3. We will describe these steps in following sections.

Bottom Line: In order to offer mobile customers better service, we should classify the mobile user firstly.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.

View Article: PubMed Central - PubMed

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.

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.

Show MeSH