Research Article
Customer Complain Detection in E-commerce Platforms using NLP
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 184 - Issue 40 |
| Published: Dec 2022 |
| Authors: Fahmida Sabur Tasmia, Arafat Habib Quraishi |
10.5120/ijca2022922508
|
Fahmida Sabur Tasmia, Arafat Habib Quraishi . Customer Complain Detection in E-commerce Platforms using NLP. International Journal of Computer Applications. 184, 40 (Dec 2022), 27-31. DOI=10.5120/ijca2022922508
@article{ 10.5120/ijca2022922508,
author = { Fahmida Sabur Tasmia,Arafat Habib Quraishi },
title = { Customer Complain Detection in E-commerce Platforms using NLP },
journal = { International Journal of Computer Applications },
year = { 2022 },
volume = { 184 },
number = { 40 },
pages = { 27-31 },
doi = { 10.5120/ijca2022922508 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2022
%A Fahmida Sabur Tasmia
%A Arafat Habib Quraishi
%T Customer Complain Detection in E-commerce Platforms using NLP%T
%J International Journal of Computer Applications
%V 184
%N 40
%P 27-31
%R 10.5120/ijca2022922508
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Online shopping has gained significant popularity in recent years. However, one major issue with online shopping is that buyers cannot physically inspect the products and so they have to rely on user reviews. In this paper, we construct a novel dataset for online reviews in the low-resourced Bengali language. Moreover, we conduct extensive experiments with strong deep learning-based baselines to benchmark the performance of such models in our dataset. We have applied RNN and Fast Text DNN to read customer’s feedback and identify areas of dissatisfaction and satisfaction. We have found that Fast Text DNN performed better then RNN with an accuracy of 74%.
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