Clustering Internet Usage Behaviours with SOM Neural Networks

被引:0
|
作者
Celenk, U. [1 ]
Ucan, O. [2 ]
机构
[1] Istanbul Univ, Elect & Elect Dept, Istanbul, Turkey
[2] Istanbul Aydin Univ, Elect & Elect Dept, Istanbul, Turkey
来源
WORLD CONGRESS ON ENGINEERING AND COMPUTER SCIENCE, WCECS 2012, VOL II | 2012年
关键词
GSM Internet usage; Internet usage behaviours; SOM neural Networks; Cluster analysis; Continuous Queries;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
According to different needs of users, there are different consumption habits. Consumption habits of people, which have the same age group or the same professions, are similar. A type of internet usage habits of people in this way is one of these habits. In recent years, developments in technology, GSM, and especially with 4G mobile internet usage have found applications in many areas of daily life. Enter to internet, wherever users need to, creates freedom. Messaging, media, finance and many different needs can be met through this connection. Users' occupation, age, gender, location, usage patterns according to different characteristics such as income level and the relevant properties are similar to each other according to the amount of internet usage (in Mb Download) connected to internet and internet usage frequency and duration of exposure can be clustered. SOM type of study, personal internet usage by artificial neural networks (data of the CDR) process and their profession, age, gender, location is to cluster usage patterns according to the values.
引用
收藏
页码:967 / 972
页数:6
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