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Dmitry Ponkin
Pág. 18 - 29
The article studies the concept and technologies of pre-trained language models in the context of knowledge engineering. The author substantiates the relevance of the issue of the existence of internalized and implicit knowledge, extracted from text corp...
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Marcos Orellana, Patricio Santiago García, Guillermo Daniel Ramon, Jorge Luis Zambrano-Martinez, Andrés Patiño-León, María Verónica Serrano and Priscila Cedillo
Health problems in older adults lead to situations where communication with peers, family and caregivers becomes challenging for seniors; therefore, it is necessary to use alternative methods to facilitate communication. In this context, Augmentative and...
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Xiu Li, Aron Henriksson, Martin Duneld, Jalal Nouri and Yongchao Wu
Educational content recommendation is a cornerstone of AI-enhanced learning. In particular, to facilitate navigating the diverse learning resources available on learning platforms, methods are needed for automatically linking learning materials, e.g., in...
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Xinlu Li, Yuanyuan Lei and Shengwei Ji
Sentiment analysis of online Chinese buzzwords (OCBs) is important for healthy development of platforms, such as games and social networking, which can avoid transmission of negative emotions through prediction of users? sentiment tendencies. Buzzwords h...
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Mourad Mars
With the recent advances in deep learning, different approaches to improving pre-trained language models (PLMs) have been proposed. PLMs have advanced state-of-the-art (SOTA) performance on various natural language processing (NLP) tasks such as machine ...
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Moreno La Quatra and Luca Cagliero
The emergence of attention-based architectures has led to significant improvements in the performance of neural sequence-to-sequence models for text summarization. Although these models have proved to be effective in summarizing English-written documents...
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Andrey Bogdanchikov, Dauren Ayazbayev and Iraklis Varlamis
The rapid development of natural language processing and deep learning techniques has boosted the performance of related algorithms in several linguistic and text mining tasks. Consequently, applications such as opinion mining, fake news detection or doc...
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Fenfang Li, Zhengzhang Zhao, Li Wang and Han Deng
Sentence Boundary Disambiguation (SBD) is crucial for building datasets for tasks such as machine translation, syntactic analysis, and semantic analysis. Currently, most automatic sentence segmentation in Tibetan adopts the methods of rule-based and stat...
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Samuel Kierszbaum, Thierry Klein and Laurent Lapasset
We consider the problem of solving Natural Language Understanding (NLU) tasks characterized by domain-specific data. An effective approach consists of pre-training Transformer-based language models from scratch using domain-specific data before fine-tuni...
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Fatemeh Gholami, Zahed Rahmati, Alireza Mofidi and Mostafa Abbaszadeh
In recent years, machine learning approaches, in particular graph learning methods, have achieved great results in the field of natural language processing, in particular text classification tasks. However, many of such models have shown limited generali...
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Viera Maslej-Kre?náková, Martin Sarnovský, Peter Butka and Kristína Machová
The emergence of anti-social behaviour in online environments presents a serious issue in today?s society. Automatic detection and identification of such behaviour are becoming increasingly important. Modern machine learning and natural language processi...
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Leonardo Ranaldi, Federico Ranaldi, Francesca Fallucchi and Fabio Massimo Zanzotto
Online users tend to hide their real identities by adopting different names on the Internet. On Facebook or LinkedIn, for example, people usually appear with their real names. On other standard websites, such as forums, people often use nicknames to prot...
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Dragos Constantin Nicolae, Rohan Kumar Yadav and Dan Tufis
Large-scale pre-trained language representation and its promising performance in various downstream applications have become an area of interest in the field of natural language processing (NLP). There has been huge interest in further increasing the mod...
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Trang Nguyen,Maxim Shcherbakov
Pág. 31 - 36
Nowadays, the use of chatbots in industry and education has increased substantially. Building the chatbot system using traditional methods less effective than the applied of machine learning (ML) methods. Before chatbot based on finite-state, rule-base, ...
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Ismael Garrido-Muñoz , Arturo Montejo-Ráez , Fernando Martínez-Santiago and L. Alfonso Ureña-López
Deep neural networks are hegemonic approaches to many machine learning areas, including natural language processing (NLP). Thanks to the availability of large corpora collections and the capability of deep architectures to shape internal language mechani...
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Yuna Hur, Suhyune Son, Midan Shim, Jungwoo Lim and Heuiseok Lim
Relation Extraction (RE) aims to predict the correct relation between two entities from the given sentence. To obtain the proper relation in Relation Extraction (RE), it is significant to comprehend the precise meaning of the two entities as well as the ...
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Andrei Paraschiv, Teodora Andreea Ion and Mihai Dascalu
The advent of online platforms and services has revolutionized communication, enabling users to share opinions and ideas seamlessly. However, this convenience has also brought about a surge in offensive and harmful language across various communication m...
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Shifeng Chen, Jialin Wang and Ketai He
The popularization of the internet and the widespread use of smartphones have led to a rapid growth in the number of social media users. While information technology has brought convenience to people, it has also given rise to cyberbullying, which has a ...
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Fahim Sufi
GPT (Generative Pre-trained Transformer) represents advanced language models that have significantly reshaped the academic writing landscape. These sophisticated language models offer invaluable support throughout all phases of research work, facilitatin...
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Weijun Pan, Peiyuan Jiang, Zhuang Wang, Yukun Li and Zhenlong Liao
In recent years, the emergence of large-scale pre-trained language models has made transfer learning possible in natural language processing, which overturns the traditional model architecture based on recurrent neural networks (RNN). In this study, we c...
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