Recommender System for Retail Domain

Abstract

Recommender system has been developed as a useful tool especially when we reached the era of big data and in the meanwhile the internet has been overwhelming with lots of choices. There is a need for people to filter the information to search for their needs and wants efficiently. E-commerce website such as Amazon and Netflix have been using recommender system to build and boost their sales through the personalization recommendation. With the success in the e-commerce area, researchers are keen on finding a method to boost traditional offline retailer sales thru the recommender system. Therefore, in this paper, we introduced the existing recommender system and discuss the method of filtering of each method. Then, we provide the overview of the recent paper in retailer and e-commerce domain to provide the insight and trends such as the filtering techniques and evaluation metric used. Several possible research direction has been discussed based on the current trends and problems. CCS Concepts• Information systems➝Information retrieval➝Retrieval tasks and goals➝Recommender systems.

Hybrid-based Research Article Recommender System

“…Online sales frequently use recommender systems, giving customers access to new information and purchasing options (Zhou et al, 2022;Chew et al, 2020). For instance, the recommender systems in Shopee and Lazada will propose products that the customer would be interested in buying.…”

A hybrid recommender system based on data enrichment on the ontology modelling

“…As such, to combine the advantages and eliminate the shortcoming of each specific method, a new group of RS named hybrid RS has emerged. According to a recent survey in 2020 5 , most of the recently proposed RS techniques fall under this group. Besides that, the most proposed hybrid RS combine at least one CF method in their system.…”