• Gaurav Mishra
• Paurnima Rokade
• Vijaya Biradar
• Pooja Khetmalis
• Prof. Gauri Virkar

Now days , Online Media and E-Commerce is widely used in world. Each and every person daily uses both social media like Facebook, Twitter, many more. In this system we combine the social media and e-commerce product for reducing the time of the each user based on recommendation and prediction system. For example we consider as an E-commerce websites using our social accounts like FB or G+, can also share our recent purchase details on the social media using the links to the product pages of e-commerce sites. Proposed System focusing on the product recommendation to the every user to share the details on e-commerce sites by leveraging the information or knowledge gained from the users’ social accounts. This will enable to assess the needs of the user in cold start situations. Cold Start technique used for avoiding the data loss in this website. Cold Start is a state when user login in to the e-commerce website for the first time and user don’t have any information about the history of purchases, shopping trends, etc. as it is not yet created or available. When user have social account information (no confidential information will be accessed) like posts, friends, shares, etc. then it can harness this to our benefit. For example, will be applying data mining algorithms to access the micro-blogs the user has created and extract the useful keywords and hence this data from the micro-blogs becomes the basis for product recommendation in cold start situations.

Cold start, Product Recommendation, E-commerce, Micro-blogs, Product Demography, Data mining, Information Search.

"Implementation on Social Media to E Commerce: Product Recommendation with Rehotting Prediction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.264-269, May-2019, Available :http://www.jetir.org/papers/JETIR1905O41.pdf

"Implementation on Social Media to E Commerce: Product Recommendation with Rehotting Prediction", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp264-269, May-2019, Available at : http://www.jetir.org/papers/JETIR1905O41.pdf