Recent Advances on Computational Linguistics and Natural Language Processing

A special issue of Computation (ISSN 2079-3197). This special issue belongs to the section "Computational Social Science".

Deadline for manuscript submissions: 30 October 2025 | Viewed by 2214

Special Issue Editors


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Guest Editor
Faculty of Engineering and IT, British University in Dubai, Dubai 345015, United Arab Emirates
Interests: artificial intelligence; arabic natural language processing; computational linguistics; machine learning

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Guest Editor
ENEA—Italian Agency for New Technologies, Energy and Sustainable Economic Development, Via E. Fermi 45, 00044 Frascati, Italy
Interests: stochastic modeling; computational physics; numerical simulation; language dynamics

Special Issue Information

Dear Colleagues,

This Special Issue on computational linguistics and natural language processing (NLP) highlights cutting-edge work that tackles theoretical and practical problems while bringing together recent developments in these quickly developing domains. The goal of this Special Issue is to present a thorough analysis of the most recent advancements, with an emphasis on creative methods and applications in a range of fields.‎

The integration of machine learning approaches with natural language processing is one of the main themes that this Special Issue explores. The papers look at how state-of-the-art methods, such as transformer models and deep learning, are applied to improve the efficiency of natural language processing (NLP) systems for tasks such as speech recognition, sentiment analysis, and machine translation.‎ The papers also discuss the impacts of these technologies on improving the accuracy and efficiency of language models, enabling more natural and human-like interactions with machines.

This Special Issue focuses on using natural language processing (NLP) in multilingual and low-resource environments. Researchers describe unique ways of processing languages with insufficient data, emphasizing the importance of cross-linguistic transfer and unsupervised learning techniques. These findings show that natural language processing (NLP) has the ability to overcome language barriers and promote global communication.‎

Moreover, this Special Issue investigates the ethical and societal consequences of the advances in computational linguistics and natural language processing. Contributors discuss potential biases in language models and the need for fair and transparent systems that prioritize user privacy and cultural diversity. The debates highlight the need for more research on the ethical use of NLP technologies in real-world applications.‎

Overall, this Special Issue offers a rich collection of research that pushes the boundaries of what is possible in computational linguistics and NLP. It serves as a valuable resource for academics, practitioners, and students interested in understanding the current state and future directions of these dynamic fields.

Prof. Dr. Khaled Shaalan
Dr. Filippo Palombi
Guest Editors

Manuscript Submission Information

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Keywords

  • computational linguistics
  • natural language processing
  • machine learning
  • deep learning
  • multilingual NLP
  • ethical AI
  • language models

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Published Papers (2 papers)

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23 pages, 7572 KiB  
Article
Arabic Temporal Common Sense Understanding
by Reem Alqifari, Hend Al-Khalifa and Simon O’Keefe
Computation 2025, 13(1), 5; https://doi.org/10.3390/computation13010005 - 28 Dec 2024
Viewed by 596
Abstract
Natural language understanding (NLU) includes temporal text understanding, which can be complex and encompasses temporal common sense understanding. There are many challenges in comprehending common sense within a text. Currently, there is a limited number of datasets containing temporal common sense in English [...] Read more.
Natural language understanding (NLU) includes temporal text understanding, which can be complex and encompasses temporal common sense understanding. There are many challenges in comprehending common sense within a text. Currently, there is a limited number of datasets containing temporal common sense in English and there is an absence of such datasets specifically for the Arabic language. In this study, an Arabic dataset was constructed based on an available English dataset. This dataset is considered a valuable resource for the Arabic community. Consequently, different multilingual pre-trained language models (PLMs) were applied to both the English and new Arabic datasets. Based on this, the effectiveness of these models in Arabic and English is compared and discussed. After analyzing the errors, a new categorization of errors was proposed. Finally, the ability of the PLMs to understand the input text and predict temporal features was evaluated. Through this detailed categorization of errors and classification of temporal elements, this study establishes a comprehensive framework aimed at clarifying the specific challenges encountered by PLMs in temporal common sense understanding (TCU). This methodology underscores the urgent need for further research on PLMs’ capabilities for TCU tasks. Full article
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18 pages, 930 KiB  
Case Report
Ontological Representation of the Structure and Vocabulary of Modern Greek on the Protégé Platform
by Nikoletta Samaridi, Evangelos Papakitsos and Nikitas Karanikolas
Computation 2024, 12(12), 249; https://doi.org/10.3390/computation12120249 - 23 Dec 2024
Viewed by 646
Abstract
One of the issues in Natural Language Processing (NLP) and Artificial Intelligence (AI) is language representation and modeling, aiming to manage its structure and find solutions to linguistic issues. With the pursuit of the most efficient capture of knowledge about the Modern Greek [...] Read more.
One of the issues in Natural Language Processing (NLP) and Artificial Intelligence (AI) is language representation and modeling, aiming to manage its structure and find solutions to linguistic issues. With the pursuit of the most efficient capture of knowledge about the Modern Greek language and, given the scientifically certified usability of the ontological structuring of data in the field of the semantic web and cognitive computing, a new ontology of the Modern Greek language at the level of structure and vocabulary is presented in this paper, using the Protégé platform. With the specific logical and structured form of knowledge representation to express, this research processes and exploits in an easy and useful way the distributed semantics of linguistic information. Full article
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