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Low-Resource Language Processing Using Improved Deep Learning with Hunter–Prey Optimization Algorithm
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1 of the 24 references listed on this page is in the Retraction Watch database as retracted (export 2026-11-11): 10.1155/2022/5211949 (notice 2023-10-11).
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Retraction Watch data via Crossref Labs, used with credit; OpenCitations Index (CC0) and Meta (CC BY 4.0);
dataset doi:10.7910/DVN/WT8VOA (CC BY 4.0).
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inferredcites →https://doi.org/10.1016/j.im.2021.103587openalex-snapshotPredicting aspect-based sentiment using deep learning and information visualization: The impact of COVID-19 on the airline industry
inferredcites →https://doi.org/10.1016/j.inffus.2020.10.019openalex-snapshotSentiment Analysis based Multi-Person Multi-criteria Decision Making methodology using natural language processing and deep learning for smarter decision aid. Case study of restaurant choice using TripAdvisor reviews
inferredcites →https://doi.org/10.1016/j.tcs.2022.06.020openalex-snapshotDeep learning and natural language processing in computation for offensive language detection in online social networks by feature selection and ensemble classification techniques
inferredcites →https://doi.org/10.1145/3605210openalex-snapshotNatural Language Processing Pretraining Language Model for Computer Intelligent Recognition Technology
inferredcites →https://doi.org/10.1145/3608949openalex-snapshotPelican Optimization Algorithm with Deep Learning for Aspect based Sentiment Analysis on Asian Low Resource Languages
inferredcites →https://doi.org/10.18653/v1/2023.semeval-1.49openalex-snapshotJCT at SemEval-2023 Tasks 12 A and 12B: Sentiment Analysis for Tweets Written in Low-resource African Languages using Various Machine Learning and Deep Learning Methods, Resampling, and HyperParameter Tuning
inferredcites →https://doi.org/10.3390/asi5010013openalex-snapshotA Novel Machine Learning Approach for Sentiment Analysis on Twitter Incorporating the Universal Language Model Fine-Tuning and SVM
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inferred← citeshttps://doi.org/10.1155/ahci/3363262openalex-snapshotExploring Emotional and Content Influences on ChatGPT’s Educational Usability Within the Field of Human–Computer Interaction
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