Research Article
Optimized Deep Learning Model for Sentimental Analysis to Improve
Consumer Experience in E-Commerce Websites
Bagiyalakshmi N1,* and A.C.Kothandaraman2
1Assistant Professor, Department of Computer Science and Engineering, Rajalakshmi Engineering
College, Thandalam, Mevalurkuppam, Tamil Nadu 602105, India.
2Associate Professor, Department of Computer Applications, Saveetha College of Liberal Arts and
Sciences (SIMATS), Chennai, Tamil Nadu,600124, India.
*Corresponding Author Name: R. Delshi Howsalya Devi. Email: drnbagiyalakshmi@gmail.com
Journal of Computer Allied Intelligence(JCAI),30 June
2024,2(3),41-54
Received: 15 May 2024 Accepted: 20 June 2024 Published: 30 June 2024
Sentiment analysis plays a pivotal role in deciphering customer sentiments from vast amounts
of unstructured data, particularly in the context of e-commerce where customer reviews are prolific. The
evolution of e-commerce reviews toward a multimodal format, including images, videos, and emojis,
introduces new dimensions to sentiment analysis. Traditional text-based models may struggle to
effectively capture sentiments expressed through non-textual elements. This paper proposed an effective
sentiment analysis model for the E-Commerce Platform to improve the user consumer experience. The
proposed method comprises Fejer Kernel filtering for data points estimation in the E-commerce dataset
points. Within the estimated data points fuzzy dictionary-based semantic word feature extraction is
performed for the estimation of features in the E-Commerce dataset. The dataset for the analysis is
computed with the Optimized Stimulated Annealing for the feature extraction and selection. The
classification of customer opinion is classified with the BERT deep learning model. The feature extracted
from the model is the opinion of consumers in the E-Commerce dataset. The classification of consumer
preference experience is based on opinion of customers in the E-commerce dataset. Simulation results
demonstrated that proposed model achieves the higher classification accuracy for the E-Commerce
platform.
Keywords: – Sentimental Analysis; Deep Learning; BERT; Fejer-Kernal; Stimulated Annealing; ECommerce.
Citation : Bagiyalakshmi N and A.C.Kothandaraman “Optimized Deep Learning Model for Sentimental Analysis to Improve Consumer Experience in E-Commerce Websites”, Journal of Computer Allied Intelligence (JCAI), vol.02, no.03, pp.41-54,2024.