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Journal of Artificial Intelligence and Data Mining، جلد ۷، شماره ۲، صفحات ۳۳۱-۳۴۰
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عنوان انگلیسی Analyzing Customers of South Khorasan Telecommunication Company with Expansion of RFM to LRFM Model
چکیده انگلیسی مقاله Telecommunication Companies use data mining techniques to maintain good relationships with their existing customers and attract new customers and identifying profitable/unprofitable customers. Clustering leads to better understanding of customer and its results can be used to definition and decision-making for promotional schemes. In this study, we used the 999-customer purchase records in South Khorasan Telecommunication Company which has been collected during a year. The purpose of this study is to classify customers into several clusters. Since the clusters and the number of their members are determined, high-consumption users will be logged out of the system and high-value customers who are missed will be identified. In this research we divided our customers into five categories: loyal, potential, new, missed and high-consumption by using the Clementine software, developing the RFM model to the LRFM model and TwoStep and k_Means algorithms. Thus, this category will be a good benchmark for company's future decisions and we can make better decisions for each group of customers in the future.
کلیدواژه‌های انگلیسی مقاله LRFM Model, TwoStep algorithm, k_Means algorithm
نویسندگان مقاله V. Babaiyan |
Department Of Computer Engineering, Birjand University of Technology, Birjand, Iran.

Seyyede A. Sarfarazi |
Department Of Computer Engineering, Birjand University of Technology, Birjand, Iran.

نشانی اینترنتی http://jad.shahroodut.ac.ir/article_1187_2c51c149ee9fdd0b4dc816a5ba235c0f.pdf
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زبان مقاله منتشر شده en
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