Journal Article10.1016/J.FUTURE.2020.08.019
Explicit aspects extraction in sentiment analysis using optimal rules combination
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TL;DR: The Whale Optimization Algorithm was improved to address rules selection problem with an improved algorithm called improved WOA (IWOA), and a new pruning algorithm has been developed to remove incorrect aspects and retain correct aspects.
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About: This article is published in Future Generation Computer Systems. The article was published on 01 Jan 2021.
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Citations
A novel LSTM–CNN–grid search-based deep neural network for sentiment analysis
TL;DR: In this article, a novel LSTM-convolutional neural networks (CNN) based grid search-based deep neural network model was proposed for sentiment analysis. And the proposed model based on hyperparameter optimization outperforms other baseline models with an overall accuracy greater than 96%.
An enhanced guided LDA model augmented with BERT based semantic strength for aspect term extraction in sentiment analysis
Manju Venugopalan,Deepa Gupta +1 more
TL;DR: This paper proposed an unsupervised approach for aspect term extraction, a guided Latent Dirichlet Allocation (LDA) model that uses minimal aspect seed words from each aspect category to guide the model in identifying the hidden topics of interest to the user.
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KnowMIS-ABSA: an overview and a reference model for applications of sentiment analysis and aspect-based sentiment analysis
TL;DR: In this paper , a new reference model for aspect-based sentiment analysis, namely the KnowMIS-ABSA model, is proposed, which is grounded on the consideration that sentiment, affect, emotion and opinion are very different concepts and that it is profoundly wrong to use the same metric and the same technique to measure them.
Improved Equilibrium Optimization Algorithm Using Elite Opposition-Based Learning and New Local Search Strategy for Feature Selection in Medical Datasets
Zenab Mohamed Elgamal,Norizan Mohd Yasin,Aznul Qalid Md Sabri,Rami Sihwail,Mohammad Tubishat,Hazim Jarrah +5 more
- 10 Jun 2021
TL;DR: In this study, an equilibrium optimization algorithm (EOA) is used to minimize the selected features from high-dimensional medical datasets and enhanced the population diversity, classification accuracy, and selected features, and increased the convergence speed rate.
52
Hybrid Binary Dragonfly Algorithm with Simulated Annealing for Feature Selection
Hamouda Chantar,Mohammad Tubishat,Mansour Essgaer,Seyedali Mirjalili +3 more
- 01 Jan 2021
TL;DR: In this article, an improved version of Dragonfly Algorithm (DA) is proposed by combining it with Simulated Annealing (SA), where the improved algorithm named BDA-SA was applied to the best solution found by Binary Dragonfly algorithm in attempt to improve its accuracy.
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