A comparative study of recommendation algorithms in e-commerce
Reshma Chavan, Debajyoti Mukhopadhyay · 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) · 2017
The recommender systems are used extensively around the world to increase sales and profits. A proper recommender system improves overall user shopping experience. In the e-commerce industry, this approach helps acquire potential market opportunities. This paper focuses on the comparison of different recommendation algorithms and provides a guideline to choose the best algorithm. Better and appropriate recommendations can be achieved by analysing a large amount of data by using Hadoop MapReduce framework, along with appropriate GUI.