دانلود مقاله ISI انگلیسی شماره 46643
عنوان فارسی مقاله

پیش بینی ریزش بهبود در صنعت مخابرات با استفاده از تکنیک های داده کاوی

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
46643 2014 19 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Improved churn prediction in telecommunication industry using data mining techniques
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Applied Soft Computing, Volume 24, November 2014, Pages 994–1012

کلمات کلیدی
مخابرات - درخت های تصمیم گیری - داده کاوی
پیش نمایش مقاله
پیش نمایش مقاله پیش بینی ریزش بهبود در صنعت مخابرات با استفاده از تکنیک های داده کاوی

چکیده انگلیسی

To survive in today's telecommunication business it is imperative to distinguish customers who are not reluctant to move toward a competitor. Therefore, customer churn prediction has become an essential issue in telecommunication business. In such competitive business a reliable customer predictor will be regarded priceless. This paper has employed data mining classification techniques including Decision Tree, Artificial Neural Networks, K-Nearest Neighbors, and Support Vector Machine so as to compare their performances. Using the data of an Iranian mobile company, not only were these techniques experienced and compared to one another, but also we have drawn a parallel between some different prominent data mining software. Analyzing the techniques’ behavior and coming to know their specialties, we proposed a hybrid methodology which made considerable improvements to the value of some of the evaluations metrics. The proposed methodology results showed that above 95% accuracy for Recall and Precision is easily achievable. Apart from that a new methodology for extracting influential features in dataset was introduced and experienced.

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