ISSN (Online) : 2456 - 0774

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ISSN (Online) 2456 - 0774

Product Recommendation for Cold-Start User usingMicroblogging Information by Connecting Social Media to E-commerce


Abstract Nowadays,almost every single person in a metropolitan daily uses both social media likeFacebook, Twitter, etc. for networking and uses internet to make huge purchasesusing e-commerce sites like Flipkart, Amazon, etc. Social commerce is a subsetof electronic commerce that involves social media, online media that supportssocial interaction and user contributions to assist online buying and sellingof products and services. Anyone can login to e-commerce websites using theirsocial accounts like Facebook or Google+. Also they share their recent purchasedetails on the social media using the sites to the product pages of e-commercesites. Focus on the product recommendation to the users on e-commerce sites byleveraging the information or knowledge gained from the user’s social accounts.This will enable to assess the needs of the user in cold start situations. ColdStart is a state when user logs in to the ecommerce website for the first timeand do not have any information about the history of purchases, shoppingtrends, etc. as it is not yet created or available. When we have users socialaccount information (no confidential information will be accessed) like posts,friends, shares, etc. then we can harness this to our benefit. Suppose, we willbe applying data mining algorithms to access the microblogs the user hascreating and extracting the useful information and hence this data from themicroblogs becomes the basis for the product recommendation in cold-startsituations.

Keywords: E-commerce,Social media, Product recommender, Product demographic, Microblogs, Cold-StartUser, Information Search.

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efore 30 th August 2019

Issue Publication   On 30 th August  2019