Saddam Imdad


Master of Science in Computer Science


Department of Computer Science

Faculty / School

Faculty of Computer Sciences (FCS)

Date of Submission



Muhammad Sarim, Visiting Faculty, Department of Computer Science

Document type

MSCS Survey Report


Data mining techniques are widely being used to extract important patterns from data to make future decisions, especially in the corporate sector. Different models are present to improve the Customer Relation Management and one of them is market segmentation. A lot of research has been done for the targeted marketing and some many clustering and classification techniques are proposed to segment the customers for targeted marketing. This paper presents a comprehensive literature review on the research work done on clustering and classification algorithms to segment the market. Articles from 2001 to 2014 which were which were related to market segmentation were reviewed carefully. Concepts related to clustering and classification techniques are also discussed in this paper and overview of market segmentation is given. Findings in this paper indicate that discriminative and descriptive models are frequently used for the market segmentation. But discriminative dominates the descriptive models due to the increase in computing speed and decrease of cost. This research survey is a guide for the future researcher for the clustering and classification techniques which are being used to market segmentation and it valuable source for academic and industry research.

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