Toward a New Hybrid Intelligent Sentiment Analysis using CNN- LSTM and Cultural Algorithms

Imtiez Fliss

2022

Abstract

In this paper, we propose a new sentiment analysis approach based on the combination of deep learning and soft computing techniques. We use the GloVe word embeddings for feature extraction. For sentiment classification, we propose to combine CNN and LSTM to decide whether the sentiment among the text is positive or negative. To tune hyperparameters, this classifier is optimized using cultural algorithms.

Paper Citation

in Harvard Style

Fliss I. (2022). Toward a New Hybrid Intelligent Sentiment Analysis using CNN- LSTM and Cultural Algorithms. In Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 1: NLPinAI, ISBN 978-989-758-547-0, pages 467-477. DOI: 10.5220/0010990400003116

in Bibtex Style

@conference{nlpinai22,
author={Imtiez Fliss},
title={Toward a New Hybrid Intelligent Sentiment Analysis using CNN- LSTM and Cultural Algorithms},
booktitle={Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 1: NLPinAI,},
year={2022},
pages={467-477},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010990400003116},
isbn={978-989-758-547-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 1: NLPinAI,
TI - Toward a New Hybrid Intelligent Sentiment Analysis using CNN- LSTM and Cultural Algorithms
SN - 978-989-758-547-0
AU - Fliss I.
PY - 2022
SP - 467
EP - 477
DO - 10.5220/0010990400003116