24   Artículos

 
en línea
Timotej Jagric and Alja? Herman    
This paper presents a broad study on the application of the BERT (Bidirectional Encoder Representations from Transformers) model for multiclass text classification, specifically focusing on categorizing business descriptions into 1 of 13 distinct industr... ver más
Revista: Information    Formato: Electrónico

 
en línea
Weiwei Yuan, Wanxia Yang, Liang He, Tingwei Zhang, Yan Hao, Jing Lu and Wenbo Yan    
The extraction of entities and relationships is a crucial task in the field of natural language processing (NLP). However, existing models for this task often rely heavily on a substantial amount of labeled data, which not only consumes time and labor bu... ver más
Revista: Agriculture    Formato: Electrónico

 
en línea
Jin-Woo Kong, Byoung-Doo Oh, Chulho Kim and Yu-Seop Kim    
Intracerebral hemorrhage (ICH) is a severe cerebrovascular disorder that poses a life-threatening risk, necessitating swift diagnosis and treatment. While CT scans are the most effective diagnostic tool for detecting cerebral hemorrhage, their interpreta... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Jinlong Wang, Dong Cui and Qiang Zhang    
With sentiment prediction technology, businesses can quickly look at user reviews to find ways to improve their products and services. We present the BertBilstm Multiple Emotion Judgment (BBMEJ) model for small-sample emotion prediction tasks to solve th... ver más
Revista: Future Internet    Formato: Electrónico

 
en línea
Somaiyeh Dehghan and Mehmet Fatih Amasyali    
BERT, the most popular deep learning language model, has yielded breakthrough results in various NLP tasks. However, the semantic representation space learned by BERT has the property of anisotropy. Therefore, BERT needs to be fine-tuned for certain down... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Yu Dai, Yuqiao Liu, Lei Yang and Yufan Fu    
Idioms are a unique class of words in the Chinese language that can be challenging for Chinese machine reading comprehension due to their formal simplicity and the potential mismatch between their literal and figurative meanings. To address this issue, t... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Yeon-Ji Park, Min-a Lee, Geun-Je Yang, Soo Jun Park and Chae-Bong Sohn    
The BioBERT Named Entity Recognition (NER) model is a high-performance model designed to identify both known and unknown entities. It surpasses previous NER models utilized by text-mining tools, such as tmTool and ezTag, in effectively discovering novel ... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Wei Zhang, Jingtao Meng, Jianhua Wan, Chengkun Zhang, Jiajun Zhang, Yuanyuan Wang, Liuchang Xu and Fei Li    
Social media is widely used to share real-time information and report accidents during natural disasters. Named entity recognition (NER) is a fundamental task of geospatial information applications that aims to extract location names from natural languag... ver más
Revista: ISPRS International Journal of Geo-Information    Formato: Electrónico

 
en línea
Huidong Tang, Sayaka Kamei and Yasuhiko Morimoto    
Text classification is widely studied in natural language processing (NLP). Deep learning models, including large pre-trained models like BERT and DistilBERT, have achieved impressive results in text classification tasks. However, these models? robustnes... ver más
Revista: Algorithms    Formato: Electrónico

 
en línea
Marios Koniaris, Dimitris Galanis, Eugenia Giannini and Panayiotis Tsanakas    
The increasing amount of legal information available online is overwhelming for both citizens and legal professionals, making it difficult and time-consuming to find relevant information and keep up with the latest legal developments. Automatic text summ... ver más
Revista: Information    Formato: Electrónico

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