Zobrazeno 1 - 10
of 118
pro vyhledávání: '"AraBERT"'
Publikováno v:
Jordanian Journal of Computers and Information Technology, Vol 10, Iss 1, Pp 1-16 (2024)
Chatbots have recently become essential in various fields, ranging from customer service and information acquisition to entertainment. The use of chatbots reduces operational costs and human errors while providing services at any time. This work pres
Externí odkaz:
https://doaj.org/article/43c2058c7fb14e85b9ffa947660785ae
Autor:
Bashar AlEsawi, Mohammed Haqi Al-Tai
Publikováno v:
Iraqi Journal for Computer Science and Mathematics, Vol 5, Iss 1 (2024)
The proliferation of fake news or misinformation, commonly referred to as fake news, has a significant effect on a global scale, as it is aimed at influencing public opinion as well as crowd decision-making. It is therefore crucial to verify the trut
Externí odkaz:
https://doaj.org/article/bc0df4f85e4f42f69f1a944d53a3b4f4
Autor:
Tahani N. Alruqi, Salha M. Alzahrani
Publikováno v:
AI, Vol 4, Iss 3, Pp 667-691 (2023)
Chatbots are programs with the ability to understand and respond to natural language in a way that is both informative and engaging. This study explored the current trends of using transformers and transfer learning techniques on Arabic chatbots. The
Externí odkaz:
https://doaj.org/article/b289cd0d53ac481f9681b43bba902bbd
Publikováno v:
Computers, Vol 13, Iss 4, p 98 (2024)
Aspect-based sentiment analysis (ABSA) is a fine-grained type of sentiment analysis; it works on an aspect level. It mainly focuses on extracting aspect terms from text or reviews, categorizing the aspect terms, and classifying the sentiment polariti
Externí odkaz:
https://doaj.org/article/846d066c0b7e4a488eabd590f7a1da38
Publikováno v:
IEEE Access, Vol 11, Pp 142062-142076 (2023)
The majority of research on the Aspect-Based Sentiment Analysis (ABSA) tends to split this task into two subtasks: one for extracting aspects, Aspect Term Extraction (ATE), and another for identifying sentiments toward particular aspects, Aspect Sent
Externí odkaz:
https://doaj.org/article/e86e810c9be8426390d485de597e6488
Publikováno v:
IEEE Access, Vol 11, Pp 132516-132531 (2023)
The performance of learning models heavily relies on the availability and adequacy of training data. To address the dataset adequacy issue, researchers have extensively explored data augmentation (DA) as a promising approach. DA generates new data in
Externí odkaz:
https://doaj.org/article/d4b36ed458034b7aa1767aa4e34a39e9
Publikováno v:
PeerJ Computer Science, Vol 9, p e1425 (2023)
Aspect-based sentiment analysis tasks are well researched in English. However, we find such research lacking in the context of the Arabic language, especially with reference to aspect category detection. Most of this research is focusing on supervise
Externí odkaz:
https://doaj.org/article/e052c00bbe5847d9b7cb1d280d8037be
Akademický článek
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Akademický článek
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Publikováno v:
IEEE Access, Vol 10, Pp 30526-30535 (2022)
The exponential growth of the internet and a multi-fold increase in social media users in the last decade have resulted in a massive growth of unstructured data. Aspect-Based Sentiment Analysis (ABSA) is challenging because it performs a fine-grain a
Externí odkaz:
https://doaj.org/article/0a1aa0b140ab4d91a445a95b3ad13d70