conference-paper

A comparative study of recommendation algorithms in e-commerce

  • 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)
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Paper overview

Abstract

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.

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Publication details

DOI
10.1109/i-smac.2017.8058331
OpenAlex
W2761911701
Document type
conference-paper
Language
EN
Source
2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)
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