An integrated approach: fake review detection using convBERT-BiLSTM classification

An integrated approach: fake review detection using convBERT-BiLSTM classification

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.

Bibliografiske detaljer
Main Authors:	Mahmud, Md. Anas, Hasan, Alina, Mahbub, Tajrian, Rafi, Navid Hasan, Faiaz, Rushayed Ali
Andre forfattere:	Rahman, Md. Khalilur
Format:	Thesis
Sprog:	English
Udgivet:	Brac University 2024
Fag:	Natural language processing Fake review detection Neural networks BERT ConvBERT BiLSTM Natural language processing (Computer science) Deep learning (Machine learning)
Online adgang:	http://hdl.handle.net/10361/22855

Lignende værker

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Quality assessment of extracted information from newspaper comment sections using natural language processing
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Sentiment classification on Bengali food and restaurant reviews
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Udgivet: (2021)

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Novel approach to detect hate speech and profanity on online platforms
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Transfer learning for natural language processing /
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Identifying hate speech of Bangla language text using natural language processing
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Intracranial hemorrhage detection using CNN-LSTM fusion model
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FakeDetect: Bangla fake news detection model based on different machine learning classifiers
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Automated image caption generator in Bangla using multimodal learning
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Multimodal human detection in disaster situations using deep learning & artificial intelligence
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NLP-based AI robot for intelligent interaction
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Deep learning approaches to EEG and fMRI data: a comparative study for sleep stage classification
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Image processing and deep learning approach to evaluate earthquake resistance of urban buildings
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Detection of fake identities on twitter using supervised machine learning
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Health trauma and well-being assistant for Bengali seniors in household: a multimodal approach
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Udgivet: (2021)