Applicability of Association Rule Mining in Recommendation System for Big Data Analysis

Nowadays, on visiting a website over the internet or logging into a social media account, it is common to see the recommendation of the products. These products or services shown as advertisements are those which a consumer has ever surfed over the internet or something similar to a past purchase. A recommendation system (RS) is to provide a suggestive description of products or services to a customer based on their past purchasing history. Since this data is humongous, i.e., big data, this approach is used to extract valuable recommendations. But, the challenge here is to provide accurate recommendations to the consumer. In addition to promoting products or services, the consumer will be interested in the recommended products during the next purchase. RS is a crucial method to strengthen the business over e-platform. This paper briefly describes the recommendation system process flow, its different filtering techniques, and the challenges faced in designing the recommendation system. Moreover, the author also discusses the role of Association Rule Mining (ARM) in creating the recommendation system for resolving the issues of the ecommerce domain. Furthermore, the applicability of ARM in RS in past research is also discussed.