Design of Social Content Recommendation System Based on Influential Ranking Algorithm

Abstract

Presently, the use of social network services (SNS) is expanding, and the amount of content that is stored and shared on SNS is also increasing. With the increase in the amount of content distributed on SNS, the time and money being spent by users to find their desired content are also increasing. To resolve this problem, there is a growing interest in recommendation systems, which recommend content that is suitable for users. The core technology of recommendation systems is the filtering technology. The most widely used filtering technology is collaborative filtering; however, it has issues such as scarcity, extensibility, transparency, and cold starting. Therefore, in this study, we have designed a recommendation system using an influential ranking algorithm to overcome these issues.