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Transformer-Based Abstractive Summarization for Reddit and Twitter: Single Posts vs. Comment Pools in Three Languages

Ivan S. Blekanov, Nikita Tarasov, Svetlana S. Bodrunova • Future Internet (2022)

Abstractive summarization is a technique that allows for extracting condensed meanings from long texts, with a variety of potential practical applications. Nonetheless, today’s abstractive summarization research is limited to testing the mo...

DOAJ Open Access (DOAJ) DOI: 10.3390/fi14030069

A rule-based stemmer for Arabic Gulf dialect

Belal Abuata, Asma Al-Omari • Journal of King Saud University: Computer and Information Sciences (2015)

Arabic dialects arewidely used from many years ago instead of Modern Standard Arabic language in many fields. The presence of dialects in any language is a big challenge. Dialects add a new set of variational dimensions in some fields like ...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jksuci.2014.04.003

Natural Language Processing

Orhan Gazi Yalçın • Apress eBooks (2020)

Natural language processing (NLP) is an interdisciplinary subfield, which has components from major fields such as linguistics, computer science, and artificial intelligence. NLP is mainly concerned with the interaction between humans and c...

OPENALEX DOI: https://doi.org/10.1007/978-1-4842-6513-0_9

Methods for Analyzing the Contents of Social Media for Health Care: Scoping Review

Jiaqi Fu, Chaixiu Li, Chunlan Zhou, Wenji Li et al. • Journal of Medical Internet Research (2023)

BackgroundGiven the rapid development of social media, effective extraction and analysis of the contents of social media for health care have attracted widespread attention from health care providers. As far as we know, most of the reviews ...

DOAJ Open Access (DOAJ) DOI: 10.2196/43349

Natural language processing

David C. Yen, William S. Davis • CRC Press eBooks (2019)

This chapter introduces key natural language processing concepts and terminology. The ultimate objective of natural language processing is to allow people to communicate with computers in much the same way they communicate with each other. ...

OPENALEX DOI: https://doi.org/10.1201/9781420049107-68

Adversarial Attacks on Deep-learning Models in Natural Language Processing

Wei Emma Zhang, Quan Z. Sheng, Ahoud Alhazmi, Chenliang Li • ACM Transactions on Intelligent Systems and Technology (2020)

With the development of high computational devices, deep neural networks (DNNs), in recent years, have gained significant popularity in many Artificial Intelligence (AI) applications. However, previous efforts have shown that DNNs are vulne...

OPENALEX Open Access DOI: https://doi.org/10.1145/3374217

Analyzing Brain Tumor Classification Techniques: A Comprehensive Survey

Pratikkumar Chauhan, Munindra Lunagaria, Deepak Kumar Verma, Krunal Vaghela et al. • IEEE Access (2024)

Classification of brain tumour is critical in medical image analysis and diagnosis as it aids in determining the affinity of cases to select treatment paths. This feature underscores the importance of accurate classification of brain tumour...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3460380

What Is Natural Language Processing?

Taweh Beysolow • Apress eBooks (2018)

Deep learning and machine learning continues to proliferate throughout various industries, and has revolutionized the topic that I wish to discuss in this book: natural language processing (NLP). NLP is a subfield of computer science that i...

OPENALEX DOI: https://doi.org/10.1007/978-1-4842-3733-5_1

Natural language processing future

M. Chandhana Surabhi • International Conference on Optical Imaging Sensor and Security (ICOSS) (2013)

Natural Language Processing is a technique where machine can become more human and thereby reducing the distance between human being and the machine can be reduced. Therefore in simple sense NLP makes human to communicate with the machine e...

OPENALEX DOI: https://doi.org/10.1109/icoiss.2013.6678407

Navigating the Ethical Terrain of AI-Generated Text Tools: A Review

Yasir Abdelgadir Mohamed, Abdul Hakim H. M. Mohamed, Akbar Khanan, Mohamed Bashir et al. • IEEE Access (2024)

This review examines the ethical, social, and technical challenges posed by AI-generated text tools, focusing on their rapid advancement and widespread adoption. An exhaustive literature search across many databases, strict inclusion/exclus...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3521945

The fluency-based semantic network of LLMs differs from humans

Ye Wang, Yaling Deng, Ge Wang, Tong Li et al. • Computers in Human Behavior: Artificial Humans (2025)

Modern Large Language Models (LLMs) exhibit complexity and granularity similar to humans in the field of natural language processing, challenging the boundaries between humans and machines in language understanding and creativity. However, ...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.chbah.2024.100103