Results 111 to 120 of about 15,771 (225)

NileTMRG at SemEval-2017 Task 4: Arabic Sentiment Analysis [PDF]

Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), 2017
Cet article décrit deux systèmes qui ont été utilisés par le NileTMRG pour traiter l'analyse du sentiment arabe dans le cadre de SemEval-2017, tâche 4. NileTMRG a participé à trois sous-tâches liées à l'arabe qui sont : Sous-tâche A (classification de la polarité des messages), Sous-tâche B (classification de la polarité des messages par sujet) et Sous-
Samhaa R. El-Beltagy, Abu Bakr Soliman, Mona El Kalamawy   +2 more
openaire   +3 more sources

Cryptocurrency Trend Prediction Through Hybrid Deep Transfer Learning

International Journal of Intelligent Systems, Volume 2025, Issue 1, 2025.
The impact of sentiment analysis of comments on social networks such as X (Twitter) on the cryptocurrency market’s behavior has been proven. Also, traditional sentiment analysis and not considering the possible aspects of tweets can cause the deep model to be misleading in predicting the price trend of cryptocurrencies.
Kia Jahanbin, Mohammad Ali Zare Chahooki, Gianni Costa   +2 more
wiley   +1 more source

Artificial Intelligence for Text Analysis in the Arabic and Related Middle Eastern Languages: Progress, Trends, and Future Recommendations

International Journal of Intelligent Systems, Volume 2025, Issue 1, 2025.
In the last 10 years, there has been a rise in the number of Arabic texts, which necessitates a more profound understanding of algorithms to efficiently understand and classify Arabic texts in many applications, like sentiment analysis. This paper presents a comprehensive review of recent developments in Arabic text classification (ATC) and Arabic text
Abdullah Y. Muaad, Md Belal Bin Heyat, Faijan Akhtar, Usman Naseem, Wadeea R. Naji, Suresha Mallappa, Hanumanthappa J., Mohamadreza (Mohammad) Khosravi   +7 more
wiley   +1 more source

An AI based cross‐language aspect‐level sentiment analysis model using English corpus

Engineering Reports, Volume 6, Issue 12, December 2024.
First, a multi‐channel XLNet (Multi‐XLNet) model is used to extract contextual information from the text. Then, in the RCNN module, the contextual features are output by the forward and reverse series GRU (BiGRU) to extract deeper emotional features. Finally, the multi‐head attention mechanism obtains text attention emotion representation.
Jing Chen, Li Pan
wiley   +1 more source

Learning for clinical named entity recognition without manual annotations

Informatics in Medicine Unlocked, 2018
Background: Named entity recognition (NER) systems are commonly built using supervised methods that use machine learning to learn from corpora manually annotated with named entities.
Omid Ghiasvand, Rohit J. Kate
doaj   +1 more source

Multiple dependence representation of attention graph convolutional network relation extraction model

IET Cyber-Physical Systems: Theory &Applications, Volume 9, Issue 3, Page 247-257, September 2024.
A new model based on graph convolutional networks, which uses a variety of representations describing dependency trees from different perspectives and combines these representations to obtain a better sentence representation for relation classification is proposed. A newly defined module is added, and this module uses the attention mechanism to capture
Zhao Liangfu, Xiong Yujie, Gao Yongbin, Yu Wenjun   +3 more
wiley   +1 more source

CCheXR‐Attention: Clinical concept extraction and chest x‐ray reports classification using modified Mogrifier and bidirectional LSTM with multihead attention

International Journal of Imaging Systems and Technology, Volume 34, Issue 1, January 2024.
Abstract Radiology reports cover different aspects from radiological observation to the diagnosis of an imaging examination, such as x‐rays, magnetic resonance imaging, and computed tomography scans. Abundant patient information presented in radiology reports poses a few major challenges.
Somiya Rani, Amita Jain, Akshi Kumar, Guang Yang   +3 more
wiley   +1 more source

Aspect-Level Sentiment Analysis through Aspect-Oriented Features

HighTech and Innovation Journal
Aspect-level sentiment analysis is essential for businesses to comprehend sentiment polarities associated with various aspects within unstructured texts.
Mikail Bin Muhammad Azman Busst, Kalaiarasi Sonai Muthu Anbananthen, Subarmaniam Kannan   +2 more
doaj   +1 more source

An NLP‐Based Framework to Spot Extremist Networks in Social Media

Complexity, Volume 2024, Issue 1, 2024.
Governments and law enforcement agencies (LEAs) are increasingly concerned about growing illicit activities in cyberspace, such as cybercrimes, cyberespionage, cyberterrorism, and cyberwarfare. In the particular context of cyberterrorism, hostile social manipulation (HSM) represents a strategy that employs different manipulation methods, mostly through
Andrés Zapata Rozo, Daniel Díaz-López, Javier Pastor-Galindo, Félix Gómez Mármol, Umit Karabiyik, Fei Xiong   +5 more
wiley   +1 more source

A Weighted Diffusion Graph Convolutional Network for Relation Extraction

Journal of Electrical and Computer Engineering, Volume 2024, Issue 1, 2024.
Currently, graph convolutional network (GCN) is widely used in relation extraction (RE) tasks. Within RE tasks in the form of directed graphs, the placement of entities in the sentence context generates a large number of remote entity nodes in the directed graph.
Jiusheng Chen, Zhenlin Li, Hang Yu, Xiaoyu Zhang, Islam Abdellah   +4 more
wiley   +1 more source