Open AccessAccessing E-Commerce Through Social Media: Recommending Cold-Start Product Using Advanced Feature Mapping Method
Author(s) -
T. Vijaya Saradhi,
V Sai Vineetha,
J Prathyusha,
Kaveti Sai Teja
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.32.15569
Subject(s) - microblogging , social media , product (mathematics) , scope (computer science) , interpersonal communication , service (business) , computer science , bridge (graph theory) , cold start (automotive) , world wide web , social network (sociolinguistics) , e commerce , business , marketing , engineering , psychology , medicine , social psychology , geometry , mathematics , programming language , aerospace engineering
As of late, the outskirts between electronic trade and informal organizations are deteriorating. Many e-commerce sites support social access mechanisms where users can log into sites utilizing their interpersonal organization accounts. Clients can also put their recently obtained products with correspondence to online business items on microblogs. In this article, we suggest another answer for a product of cold launch crossed, which aims to furnish clients of ecommerce sites with long range interpersonal communication locales in situations of "cold start" which have been studied very rarely. A great problem is how to gain influence through information long range interpersonal communication to offer cross-start basic products. We recommend that users use social networking websites and ecommerce websites as social networking capabilities on the map as a bridge on the map, another representation of product offerings. Specifically, we offer using user-generated and product-specific presentations of e-commerce sites that use regular neural networks and then use modified degraded trees to convert users' social network functions investments. We then develop a matrix factor approach based on features that can be used to invest in the cold start initiated by the user. The experimental results of China's largest microblogging service, SINAWEIBO and Jing Dong's biggest B2C ecommerce site have demonstrated the adequacy of the proposed scope.