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E-commerce Product Categorization Using Big Data Analytics

Year 2021, Volume: 1 Issue: 2, 1 - 8, 30.09.2021

Abstract

E-commerce platforms need to have a well-managed online product catalog to make products easily accessible. However, the organization of catalog and categorization of products can be time-consuming due to the large volume of product data in e-commerce. In this direction, our study aims to develop an accurate categorization of product data with the adoption of big data analytics. Accordingly, various machine learning algorithms (Support Vector Machine, Naive Bayes, and Stochastic Gradient Descent) were utilized to organize online catalogs from Spark MLLib. Performed classifiers were trained and tested on product catalog data collected from a fashion retailer in Turkey, Boyner Group, which combines cutting-edge digital services with a vast network of exciting stores.

References

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There are 14 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Research Articles
Authors

Sedat Usluoğlu This is me

Deniz Kılınç This is me

Fatma Bozyiğit This is me

Publication Date September 30, 2021
Published in Issue Year 2021 Volume: 1 Issue: 2

Cite

APA Usluoğlu, S., Kılınç, D., & Bozyiğit, F. (2021). E-commerce Product Categorization Using Big Data Analytics. Artificial Intelligence Theory and Applications, 1(2), 1-8.