摘要(英) |
With wireless internet access in the growing population and the increasing popularity of wireless infrastructure, the number of mobile internet has been significant growth. But for the past habit of using the fixed-line broadband users, they only have the choice of a telecommunication company. Now there are more telecommunication companies can be compared and the rate of charging are more than the past. Due to too many different calculation methods, it make user become confuse. As result of this situation, telecommunication company’s market of wireless internet does not make high profit with the use of mobile internet population growth. So this study use Agglomerative Fuzzy K-Means clustering analysis with the customer’s past internet behavior, such as: the motives of using internet、the frequency of connect internet ... and so on. Those data are collected by the telecommunication company which is the case in this study .This study also use customers basic properties, such as: income, sex ... and so on .By using descriptive statistical methods to identify customer groups of differences in internet behavior. Use those different attributes become a indicator. It will compare with telecommunication company’ expert, then we can get the recall and precision of this indicator. The indicator can supposition the time of customer may use mobile internet and suitable charging rate. So salesperson can ask the questions about the indicator in the first place. Salesperson can use this indicator analysis to avoid the Analysis of the time delay that due to the customer’s unreasonably. It can increase the quantity of case handle by salesperson by reducing the processing time of cases and the result may increase the company’s performance.
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參考文獻 |
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