A REVIEW OF DIFFERENT DATA MINING TECHNIQUES IN CUSTOMER SEGMENTATION

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PARSA KORD ASIABI TANNANE; TAVOLI REZA

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Journal Paper

Paper Information

Journal: JOURNAL OF ADVANCES IN COMPUTER RESEARCH Year:2015 | Volume:6 | Issue:3 (21) Page(s): 51-64

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Title

A REVIEW OF DIFFERENT DATA MINING TECHNIQUES IN CUSTOMER SEGMENTATION

Author(s)

PARSA KORD ASIABI TANNANE | TAVOLI REZA | Issue Writer Certificate

Keywords

ORGANIZATION

CRM

DATA MINING

CUSTOMER SEGMENTATION

Abstract

Customers are the most valuable asset of an ORGANIZATION. Due to high contest in the business field, it is necessary to regard the Customer Relationship Management (CRM) of the enterprise. DATA MINING and Machine Learning methods been utilized by businesses in recent years in order to improve CRM. CRM is the strategy for building, managing, and strengthening loyal and long lasting customer relationship. DATA MINING is the knowledge discovery process by analyzing the large volumes of data from various perspectives and summarizing it into useful information. DATA MINING have a several techniques in CRM but in this article we present the basic classification and clustering techniques that used. The target of this survey is to provide extensive review of different classification and clustering techniques in CUSTOMER SEGMENTATION.

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APA: Copy

PARSA KORD ASIABI, TANNANE, & TAVOLI, REZA. (2015). A REVIEW OF DIFFERENT DATA MINING TECHNIQUES IN CUSTOMER SEGMENTATION. JOURNAL OF ADVANCES IN COMPUTER RESEARCH, 6(3 (21)), 51-64. SID. https://sid.ir/paper/328806/en

Vancouver: Copy

PARSA KORD ASIABI TANNANE, TAVOLI REZA. A REVIEW OF DIFFERENT DATA MINING TECHNIQUES IN CUSTOMER SEGMENTATION. JOURNAL OF ADVANCES IN COMPUTER RESEARCH[Internet]. 2015;6(3 (21)):51-64. Available from: https://sid.ir/paper/328806/en

IEEE: Copy

TANNANE PARSA KORD ASIABI, and REZA TAVOLI, “A REVIEW OF DIFFERENT DATA MINING TECHNIQUES IN CUSTOMER SEGMENTATION,” JOURNAL OF ADVANCES IN COMPUTER RESEARCH, vol. 6, no. 3 (21), pp. 51–64, 2015, [Online]. Available: https://sid.ir/paper/328806/en

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