Comparative study of texts of advertisements by online local and foreign food industries companies through text mining and clustering technique

As these days large number of businesses use online shops for selling their products, for more effective management of their activities and better serving their customers, analysis of the text of their commercials which somehow reflects their mandate, has become very important.
In this research work, 29 interesting advertisements by local online suppliers of goods and 24 foreign online shops have been studied. For pre- processing and amalgamation of the texts, the clustering technique has been employed and for obtaining the K mean algorithm, text mining has been used.
Meanwhile, for placing in separate cluster and finding out the most important roots in each cluster, Multiple Attribute Decision Making (MADM) has been employed so that in addition to specifying the content of each commercial, differences and similarities of these two approach to become evident.
By comparing the local clusters with foreign ones, it became evident that the local companies mostly concentrate on concept such as “product” and “generalization” but foreign companies pay more attention to concept like “Customer Orientation”.