RSS Using Social Networks User Profile

Abstract

E-commerce application in recent days are gaining more importance due to its worldwide services and user-friendly applications. Some of the social networking applications are being backbone of e-commerce applications help in its functioning. With this, the number of e-commerce applications are being associated with social networking site and their user profiles. E-commerce sites use this social networking sites as service providers to their customers associated with their social networking profiles. In these online transactions, social networking sites act as third-party service providers to its users with respect to e-commerce interactions. Social networking sites acting as third-party service providers should be careful about users type, their behaviour and services that they provide. Users choosing their services should also be careful about what to choose and what not to choose. In this three-tier interactions, trust plays a very important role. Trust on any service providers should be evaluated to stay away from online fraudulent activities. User interacting through these applications should always be able to decide between the trusted services and fraud services. Hence, service selection in social networking is proposed with the help of Refined Service Selection (RSS) algorithm using social networks user profiles. Implementation is done with the help of real data set and found that the accuracy of RSS is more when compared with the existing algorithms.