Recommendation System in Business Intelligence Solutions for Grocery shops: Challenges and Perspective

被引：1

作者：

Mohan, Atul ^{[1
]}

Abdelrazeq, Anas ^{[1
]}

Hees, Frank ^{[1
]}

机构：

[1] Rhein Westfal TH Aachen, Chair Informat Management Mech Engn IMA, Dennewartstr 27, D-52068 Aachen, Germany

来源：

3RD INTERNATIONAL CONFERENCE ON E-COMMERCE, E-BUSINESS AND E-GOVERNMENT, ICEEG 2019 | 2019年

关键词：

E-Commerce; Business Intelligence; Recommendation System; Collaborative Filtering; INFORMATION;

D O I：

10.1145/3340017.3340030

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

With the surge in digital platforms and extension of e-commerce, the field of recommendation has been a topic of interest not only for the data scientist but deemed important by the business experts to enhance the user-centric services. A large number of retail & service-oriented companies such as Amazon, Netflix, Goodreads, and Spotify etc. use Business Intelligence (BI) and recommendation systems to provide users with various choices of products based on their interest. Evidently, such a customized user-experience not only provide them with a better service, but also enables the companies to understand customer behavior and enhance their business. The aim of this paper is to introduce a recommendation system in the business intelligence platform to a new-system where no user's previous interaction information is available. We present an exploratory study of implementing recommendation system in the project SmartEmma, a grocery shop application in Aachen, funded by EFRE.NRW, European Union and WIRTSCHAFT.NRW.

引用

下载

页码：53 / 57

页数：5

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