Weighted Ensemble LSTM Model with Word Embedding Attention for E-Commerce Product Recommendation
Nowadays, the proliferation of social media and e-commerce platforms is largely due to the development of internet technology. Additionally, consumers are used to the idea of using these platforms to share their thoughts and feelings with others through text or multimedia data. However, it is diffic...
Main Authors: | Prashant Sharma, Vijaya Ravindra Sagvekar |
---|---|
Format: | Article |
Language: | English |
Published: |
Croatian Communications and Information Society (CCIS)
2023-12-01
|
Series: | Journal of Communications Software and Systems |
Subjects: | |
Online Access: | https://jcoms.fesb.unist.hr/10.24138/jcomss-2023-0126/ |
Similar Items
-
Lexicon-Enhanced LSTM With Attention for General Sentiment Analysis
by: Xianghua Fu, et al.
Published: (2018-01-01) -
A New Sentiment-Enhanced Word Embedding Method for Sentiment Analysis
by: Qizhi Li, et al.
Published: (2022-10-01) -
Improving Arabic Sentiment Analysis Using LSTM Based on Word Embedding Models
by: Youssra Zahidi, et al.
Published: (2023-08-01) -
Sentiment Analysis on Roman Urdu Students’ Feedback Using Enhanced Word Embedding Technique
by: Noureen, et al.
Published: (2024-02-01) -
Refined Global Word Embeddings Based on Sentiment Concept for Sentiment Analysis
by: Yabing Wang, et al.
Published: (2021-01-01)