Best Offer Recommendation Service

被引:0
|
作者
Javkar, Kiran Gajanan [1 ]
Vora, Siddharth Hasmukh [1 ]
Rodge, Amit Someshwarrao [1 ]
Bose, Joy [1 ]
Sharma, Hitesh [1 ]
机构
[1] Samsung R&D Inst India, Web Serv Grp, Bangalore, Karnataka, India
关键词
Ecommerce; Coupon aggregators; recommendation system; cloud service;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
There are multiple online offer aggregators, which can aggregate deals, coupons and offers from multiple parties. However, these aggregators generally cannot determine the best deal/s available among the existing deals. Many deals or coupons specify the percentage of discount or cashback on purchase of the item using the user's credit card, where the percentage varies between different cards. This makes it difficult to determine the best offer for a given credit card. In this paper we propose a service which can determine which offers would be relevant for a user with a given profile and/or online payment mechanism. The cloud server stores relevant data about available offers using crawlers and publicly available APIs, and given a desired product determines the best set of coupons or offers available given a user profile and payment mechanism such as credit card. This enables the service to recommend the best deals to the user. We have implemented a simple proof of concept for our service using a cloud server component and a component that is part of the web browser application on a device. We also discuss a revenue sharing model for our service.
引用
收藏
页码:2430 / 2436
页数:7
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