Survey on Connecting Social Media to E-Commerce: Cold-Start Product Recommendation Using Microblogging Information

Abstract

In recent years, a point that indicates where two things become different is confused. Many e-commerce websites supports the mechanism of social login where users can sign in by using their social networking identities such as facebook or twitter. User can post their newly purchased things on microblog which means posting frequent brief messages about personal activities with link to the e-commerce product websites. Cold start is one of the most challenging and potential problem .The drawback in this is that the system cannot produce the sufficient information which was gathered earlier . .In this paper we propose a different solution for cross-site cold-start product recommendation which aims to recommend products from e-commerce websites to users at social networking sites in “cold-start” situations, a problem which has rarely been explored before. We planned to use the users who have social networking accounts and have made purchases on e-commerce websites) as a bridge to map users’ social networking features to another feature representation for product recommendation. In specific, we propose learning both users’ and products’ (called user embeddings and product embeddings, respectively)