Abstract
The current study primarily aims to develop a dictionary system for tracing mobile phone numbers for call centers of mobile communication companies. This system tries to save the numbers using a digital search tree in order to make the processes of searching and retrieving customers’ information easier and faster. Several shrubs that represent digits of the total phone numbers will be built through following the phone number digits to be added to the dictionary, with the owner name being at the last node in the tree. Thus, by such searching process, every phone number can be tracked digit-by-digit according to a required path inside its tree, until reaching the leaf. Then, the value stored in the node, that represents the name of phone number’s owner, is returned. Consequently, the amount of memory required to store data will be reduced and data retrieval will be faster.
Highlights
There were improvements in all technical features for smartphones
Very fast processors and storage units are used for mobile phones
For smart phones and mobile devices, the algorithms designed to run on desktop computers are not considered as good choice
Summary
There were improvements in all technical features for smartphones. Relatively very fast processors and storage units are used for mobile phones. Some methods are applicable to reduce the computational costs They are typically employing feature hashing, performing nearest neighbor searches using Hamming distances. Pregibon and Cortes (2001) developed signature-based methods to produce a mark from an information stream of call detail records to briefly portray the calling conduct of clients. They utilized peculiarity identification to gauge the bizarreness of another call compared with a specific record [10, 11]. Adeyemo and Oyeniyi (2015) developed a model in banking sectors using data mining techniques to analyze customer churn In that model, they utilized simple Knee Means (KMeans) in the clustering stage and a rule-based algorithm for the rule generation stage [13]. The phone numbers length in this sample is 10 digits
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