Design Context Aware Activity Recommender System for Iranian Customer Mind Activism in Online Shopping

Abstract

E-commerce has made life simple and innovative of individuals and groups. Nowadays, social networks are widely used by everyone. So, it is necessary to do appropriate and situation aware activities in these networks to gain benefits, In this research, a context aware recommender system has modeled for using in social networks focus on Iranian customer mind activism in online shopping. This system makes its recommendations for user based on behavior and activities of her friends in the same situation in social network. In other word, this modeled recommender system uses collaborative filtering algorithm. All the connections of user in social network, containing direct and indirect, are considered for recommending by recommender system; but, based on connection type and its distance to user, proportional factor is assigned. On the other, In this research we study the consumer behavior in online shopping of electronics especially in Iran. Primary data was collected through the questionnaire survey and by emails from personal contacts in two major cities of Iran. Price, time saving and convenience were identified as important factors which lead to certain buying behavior in online shopping.