Connecting Social Media to E-Commerce Cold-Start Product Recommendation using Information


YEAR :2016



In recent years, the boundaries between e-commerce and social networking have become increasingly blurred. Many e-commerce websites support the mechanism of social login where users can sign on the websites using their social network identities such as their Facebook or Twitter accounts. Users can also post their newly purchased products on microblogs with links to the e-commerce product web pages. In this paper we propose a novel 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. A major challenge is how to leverage knowledge extracted from social networking sites for cross-site cold-start product recommendation.


•System : Dual core.
•Hard Disk : 40 GB.
•Floppy Drive : 1.44 Mb.
•Monitor : 15 VGA Colour.
•Mouse : Logitech.
•Ram : 4 GB.


•Operating system : Windows XP/7/10/11.
•Coding Language : JAVA
•Data Base : MYSQL


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