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Academic Articles & Research Papers
Showing 20 of 20 academic articles
Xavier Vasques • Wiley eBooks
(2024)
This book chapter focuses on natural language processing (NLP) and covers various applications such as classifying messages as spam or ham, sentiment analysis, and the use of Bidirectional Encoder Representations from Transformers (BERT). T...
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DOI: https://doi.org/10.1002/9781394220649.ch4
Santanu Pattanayak • Apress eBooks
(2022)
In the modern age of information and analytics, natural language processing (NLP) is one of the most important technologies out there. Making sense of complex structures in language and deriving insights and actions from it are crucial from...
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DOI: https://doi.org/10.1007/978-1-4842-8931-0_4
Luciano Ignaczak, Guilherme Goldschmidt, Cristiano André da Costa, Rodrigo da Rosa Righi • ACM Computing Surveys
(2021)
The growth of data volume has changed cybersecurity activities, demanding a higher level of automation. In this new cybersecurity landscape, text mining emerged as an alternative to improve the efficiency of the activities involving unstruc...
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DOI: https://doi.org/10.1145/3462477
Xieling Chen, Haoran Xie, Fu Lee Wang, Ziqing Liu et al. • BMC Medical Informatics and Decision Making
(2018)
BACKGROUND: Natural language processing (NLP) has become an increasingly significant role in advancing medicine. Rich research achievements of NLP methods and applications for medical information processing are available. It is of great sig...
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DOI: https://doi.org/10.1186/s12911-018-0594-x
PMC: 5872501
Yuan Huang, Zhixing Li, Wei Deng, Guoyin Wang et al. • CAAI Transactions on Intelligence Technology
(2021)
Abstract Relation extraction between entity pairs is an increasingly critical area in natural language processing. Recently, the pre‐trained bidirectional encoder representation from transformer (BERT) performs excellently on the text class...
DOAJ
Open Access (DOAJ)
DOI: 10.1049/cit2.12033
Cyrille YetuYetu Kesiku, Andrea Chaves-Villota, Begonya Garcia-Zapirain • Information
(2022)
The classification of biomedical literature is engaged in a number of critical issues that physicians are expected to answer. In many cases, these issues are extremely difficult. This can be conducted for jobs such as diagnosis and treatmen...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/info13100499
Aditya Malte, Pratik Ratadiya • arXiv (Cornell University)
(2019)
In this paper, we present a study of the recent advancements which have helped bring Transfer Learning to NLP through the use of semi-supervised training. We discuss cutting-edge methods and architectures such as BERT, GPT, ELMo, ULMFit amo...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1910.07370
Zhijing Jin, Rada F. Mihalcea • Springer eBooks
(2022)
Abstract Language is the medium for many political activities, from campaigns to news reports. Natural language processing (NLP) uses computational tools to parse text into key information that is needed for policymaking. In this chapter, w...
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DOI: https://doi.org/10.1007/978-3-031-16624-2_7
Aziliz Le Glaz, Yannis Haralambous, Deok-Hee Kim-Dufor, Philippe Lenca et al. • Journal of Medical Internet Research
(2020)
BACKGROUND: Machine learning systems are part of the field of artificial intelligence that automatically learn models from data to make better decisions. Natural language processing (NLP), by using corpora and learning approaches, provides ...
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DOI: https://doi.org/10.2196/15708
PMC: 8132982
Sumaya Mustafa, Mariwan Hama Saeed • Journal of Electrical Systems and Information Technology
(2025)
Abstract Artificial intelligence (AI) models have demonstrated significant success in classifying various types of text. However, the complex nature of these models often complicates the interpretability of their classifications. To address...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s43067-025-00273-2
Yasha Hasija, Rajkumar Chakraborty • CRC Press eBooks
(2021)
Natural language processing is a fast-evolving field with popular applications in language translation, speech recognition, text classification, and summarization of text, among others. The central aspect of NLP is vectorizing text data. Te...
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DOI: https://doi.org/10.1201/9781003090113-15-15
Yue Zhang, Zhiyang Teng • Cambridge University Press eBooks
(2020)
With a machine learning approach and less focus on linguistic details, this gentle introduction to natural language processing develops fundamental mathematical and deep learning models for NLP under a unified framework. NLP problems are sy...
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DOI: https://doi.org/10.1017/9781108332873
LIU Yao, QIN Xun, LIU Tianji • Jisuanji kexue
(2024)
To address the issue of re-analyzing and repeating development of natural language processing tools and resource ana-lysis plugins when new requirements arise during project development,this paper proposes a business-oriented on-demand reso...
DOAJ
Open Access (DOAJ)
DOI: 10.11896/jsjkx.230800191
Xinhui Liu, Jifa Chen, Qiubo Huang • Applied Sciences
(2025)
With the explosion of information, the amount of text data has increased significantly, making text categorization a central area of research in natural language processing (NLP). Traditional machine learning methods are effective, but deep...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app15084236
Rada F. Mihalcea, Dragomir Radev • Cambridge University Press eBooks
(2011)
Graph theory and the fields of natural language processing and information retrieval are well-studied disciplines. Traditionally, these areas have been perceived as distinct, with different algorithms, different applications and different p...
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DOI: https://doi.org/10.1017/cbo9780511976247
Akshay Kulkarni, Adarsha Shivananda • Apress eBooks
(2019)
Implement natural language processing applications with Python in this problem-solution book. Here, coding exercises will help you to quickly deploy natural language processing techniques, such as text classification, parts of speech identi...
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DOI: https://doi.org/10.1007/978-1-4842-4267-4
Shervin Minaee, Nal Kalchbrenner, Erik Cambria, Narjes Nikzad-Khasmakhi et al. • ACM Computing Surveys
(2021)
Deep learning--based models have surpassed classical machine learning--based approaches in various text classification tasks, including sentiment analysis, news categorization, question answering, and natural language inference. In this art...
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Open Access
DOI: https://doi.org/10.1145/3439726
Kamran Kowsari, Donald E. Brown, Mojtaba Heidarysafa, Kiana Jafari Meimandi et al. • International Conference on Machine Learning and Applications
(2017)
Increasingly large document collections require improved information processing methods for searching, retrieving, and organizing text. Central to these information processing methods is document classification, which has become an importan...
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Open Access
DOI: https://doi.org/10.1109/icmla.2017.0-134
Zhi He, Chengle Zhou, Liwei Zou, Suhong Zhou et al. • International Journal of Digital Earth
(2025)
Accurately monitoring disaster effects is a crucial task in relief efforts (e.g. typhoon rescue). Social media data plays a vital role in disaster management, while deep learning-based methods gain more attention in typhoon disaster researc...
DOAJ
Open Access (DOAJ)
DOI: 10.1080/17538947.2025.2517790
François Chollet (2017)
DESCRIPTION Deep learning is applicable to a widening range of artificial intelligence problems, such as image classification, speech recognition, text classification, question answering, text-to-speech, and optical character recognition. D...
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