Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 132 for “"Bert"”.
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Microbial named entity recognition using BERT models
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2024-08-01
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Með bert á milli og „iPod“ í eyrunum
Markmið þessarar rannsóknar var að skoða hver áhrifin verða af komu hinnar fjölmennu Aldamótakynslóðar inn á vinnumarkaðinn á næstu árum. Gengið var út frá því að skoða sérstaklega hvers einstaklingar af þessari kynslóð vænta og hvað mögulega kann að breytast á vinnustöðum með komu þeirra þangað …
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"Binaural sound source localization in humanoid ""bert"" robot"
Made available in DSpace on 2017-08-10T19:15:08Z (GMT). No. of bitstreams: 2 KIM-THESIS-2017.pdf: 914718 bytes, checksum: a47b367925809208eb1ebf030fcddb09 (MD5) LICENSE.txt: 4205 bytes, checksum: 8531ee359004f1045fcb8b4645b25391 (MD5) Previous issue date: 2017-04-19
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Enhancing E-commerce Dataset recommendations using BERT and Named Entity Recognition
… Document Frequency (TF-IDF) alongside BERT embeddings to capture both keyword relevance and semantic context. This approach enhances recommendation precision, making EDMRec especially suitable for complex e-commerce queries. Experimental evaluations confirm EDMRec’s effectiveness, with …
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Performance evaluation of text augmentation methods with BERT on imbalanced datasets
… Word2Vec and WordNet augmentation methods with BERT fine-tuning on datasets of various sizes (e.g., 500, 1,000, and 5,000 training documents) and imbalance ratios (e.g., 4:1 and 9:1). It compares them with other methods for imbalanced data, including boosting, SMOTE, and simple oversampling, …
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BERT-Based Intrusion Detection System for RF Jamming Attacks in Vehicular Network
… of four pre-trained transformer architectures—BERT, RoBERTa, DistilBERT, and ALBERT—fine-tuned for the multi-class classification of interference, smart jamming, and constant jamming attacks under varying vehicular speeds (25 m/s and 15 m/s). These models are systematically compared against …
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Leverage Fusion of Sentiment Features and Bert-based Approach to Improve Hate Speech Detection
… and among the ways people have studied, the Bert-based approach is promising and thus dominates SemEval-2019 Task 6, a hate speech detection competition. In this work, the method of fusion of sentiment features and Bert-based approach is proposed. The classic Bert architecture for hate speech …
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Development and Preliminary Testing of an Online Brief Emotion Regulation Training (BERT) Program for Emerging Adults
… regulation training program for emerging adults (BERT) was developed and tested. Phase 1 focused on program development. Phase 2 utilized the brainwriting premortem method to refine program content. Undergraduate students (n = 12) attended four focus groups presenting initial program content. Four …
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Analyzing the Impact of Social Media Buy Recommendations on Saudi Stock Market Reactions: A Bert-Based Sentiment and Network Analysis Approach
<p>Social media has become part of the daily rhythm of financial markets, its actual influence on prices remains debated. This dissertation examines whether buy recommendations posted by Saudi-focused social media analysts on Twitter/X are associated with short-term stock market reactions in the …
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Shared Context through Multi-Level Attention Transformers for Text Classification
… larger, deeper, more complicated; for example, BERT has 340 million parameters, Turing NLG is 17billion parameters, and GPT-3 is about 175 billion parameters. Understanding their implications requires the immense computational ability to process the text corpus during both training and …
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Conversation understanding and realistic artificial crash data generation with deep learning
… about conversations. We propose Formality-BERT which is a BERT-based model for sentence formality prediction. Formality-BERT is trained on a public dataset that contains four genres of text and outperforms existing models by 14 points on the Spearman correlation between predicted formality …
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Empirical Study on Improving Hate Speech Detection: Novel BERT based One-Versus-All Classification Approach (BOVAC) with a Novel Performance Metric: Global Performance (GP)
… my thesis in which: I explore an approach I call BERT-based one-versus-all text classification (BOVAC) for improving the task of hate speech detection. The performance of the proposed approach is assessed based on an empirical study on a dataset which was previously constructed, cleaned and …
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A Study on the Impact of Transfer Learning for Deception Detection
… the target dataset and found that this improved BERT performance. Finally, we explored the effect that combining embeddings generated by separate BERT models fine-tuned on separate deception datasets has on performance and saw several examples of improvement in baseline accuracy. Furthermore, the …
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Fine-grained sentiment analysis for customer review
… a semi-supervised approach using pre-trained BERT model to conduct the fine-grained aspect sentiment analysis, and tests it on the benchmark dataset SemEval2014. Our proposed Sentiment Mask Enhanced BERT pre-training and Multi-Token classification (SME-BERT-MT) model consists of two parts, a …
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Relation extraction: exploring syntax parsing and constructing it as attention-like structure
… parsing and recent state of arts of syntax-aware BERT [1] related models, we construct a syntax mechanism to convert syntax tree structure to matrixes and apply on the finetuning process of SyntaxBERT [2] and syntax-aware -local-attention attention BERT (SLA) [3] to strengthen their ability to …
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Automated Assessment of Psychiatric Patients Using Medical Notes
… severity level. Two classifiers are considered: BERT PDM and Clinical BERT PDM. The evaluation of these classifiers showed that the BERT PDM delivered the best performance. The PDMs developed using the BERT PDM can assign medical notes from each encounter to a severe impairment level with a …
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Domain-agnostic named entity recognition on unstructured text
… with the advent of deep learning models like BERT which are able to capture textual semantics very well. In this work, we present a detailed study approaching the NER task from three different perspectives, namely, sequence labeling, question answering (QA), and span-based classification. We …
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A Knowledge Graph based Method on Language Understanding for Customer Service
… we explore a new model named <strong>Hierar-BERT-RCNN</strong> to recognize and classify vague question in hierarchical multi-label classification step. This model outperforms over hierarchical baseline models (BERT, BERT-CNN, BERT-DPCNN) on DuEE dataset on average 0.83% higher in main level …
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Misinformation Identification Using Natural Language Processing
… dataset. The models that were evaluated are BERT (Bidirectional Encoder Representations from Transformers), DistilBERT, XLNet (Generalized Autoregressive Pretraining for Language Understanding), ALBERT (A Lite BERT), and RoBERTa (Robustly Optimized BERT Pre-training Approach). The first set …
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