Analysis of Student Sentiment Level using Perceptual Neural Boltzmann Machine Learning Approach for E-learning Applications-Reference-Cited by-同舟云学术

Analysis of Student Sentiment Level using Perceptual Neural Boltzmann Machine Learning Approach for E-learning Applications

Published:2022-07-20 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Inventive Computation Technologies (ICICT)
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Author:

Singh Laishram Kirtibas¹,Renuga Devi R.¹

Affiliation:

1. Vels Institute of Science, Technology and Advanced Studies (VISTAS),Department of Computer Science,Chennai,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9850395/9850438/09850860.pdf?arnumber=9850860

Reference20 articles.

1. Sentiment Research on Student Feedback to Improve Experiences in Blended Learning Environments;kavitha;International Journal of Innovative Technology and Exploring (IJITEE),2019

2. Unsupervised Genre-Based Multidomain Sentiment Lexicon Learning Using Corpus-Generated Polarity Seed Words

3. Evaluation of Sentiment Analysis in Finance: From Lexicons to Transformers

4. Two-Level LSTM for Sentiment Analysis With Lexicon Embedding and Polar Flipping

5. Modified fuzzy sentiment analysis approach based on user ranking suitable for online social networks

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