The Effect of Clustering in the Apriori Data Mining Algorithm: A Case Study

Yilmaz N., Alptekin G. I.

World Congress on Engineering (WCE 2013), London, Canada, 3 - 05 July 2013, pp.1611-1612 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • City: London
  • Country: Canada
  • Page Numbers: pp.1611-1612
  • Galatasaray University Affiliated: Yes


Many organizations collect and store data about their customers, suppliers and business partners. However, much of the useful marketing insights are hidden in that enormous amount of data. Data mining is the process of searching and analyzing data in order to find potentially useful information. Although data mining consists of a broad family of computational methods and algorithms, for this study, we have chosen the Apriori algorithm as the basis of the data analysis framework. The objective of the paper is to present the effect of clustering the data onto the association rules. Hence, we have compared the results of two different approaches: Finding association rules without consumer segmentation, and with consumer segmentation. The data analysis framework is applied to the data of mobile operating systems' users. By extracting most important information from consumer data, we claim that this framework directs providers offer the right product/advertisement to the right consumer.