Search for Articles:

Recently Downloaded: Paper ID: ART20193820, Total 179 Articles Downloaded Today



Connecting Social Media to E-Commerce Product Recommendation using Top-K

Nisha T

Abstract: Now a days online shopping has achieved a tremendous popularity within very less amount of time. Recently few ecommerce websites has been developed their functionalities to a extent such that they recommend the product for their users referring to the connectivity of the users to the social media and provide direct login from such social media such as facebook, Twitter, whatsapp. Recommend the users that are totally new to the website client novel solution for cross-site cold-start product recommendation that aims for recommending products from e-commerce websites. In specific propose learning both users and products feature representations from data collected from e-commerce websites using recurrent Top-K to transform user?s social networking features into user embeddings. The survey paper develops a Top-k approach which can manipulate the learnt user implanting for cold-start product recommendation.

Keywords: Datamining,E-Commerce,Social Media, Top-K

Country: India, Subject Area: Computer Engineering

Pages: 868 - 872

Edition: Volume 8 Issue 5, May 2019

How to Cite this Article?

Nisha T, "Connecting Social Media to E-Commerce Product Recommendation using Top-K", International Journal of Science and Research (IJSR), https://www.ijsr.net/archive/v8i5/show_abstract.php?id=ART20197796, Volume 8 Issue 5, May 2019, 868 - 872

Download PDF


Viewed 17 times.

Downloaded 14 times.