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Academic Articles & Research Papers
Showing 20 of 193 academic articles
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
Pramod Kumar Singh • Apress eBooks
(2018)
This chapter uncovers some of the basic techniques to tackle text data using PySpark. Today's textual form of data is being generated at a lightning pace with multiple social media platforms offering users the options to share their opinion...
OPENALEX
DOI: https://doi.org/10.1007/978-1-4842-4131-8_9
Ray Oshikawa, Qian, Jing, William Yang Wang • arXiv (Cornell University)
(2018)
Fake news detection is a critical yet challenging problem in Natural Language Processing (NLP). The rapid rise of social networking platforms has not only yielded a vast increase in information accessibility but has also accelerated the spr...
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Open Access
DOI: https://doi.org/10.48550/arxiv.1811.00770
S. Meera, S Geerthik • Wiley eBooks
(2022)
The AI approach applies to natural language processing. The AI communication approach uses intelligent systems. These intelligent systems, such as English, use natural languages. The process of Natural Language required a smart machine such...
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DOI: https://doi.org/10.1002/9781119821809.ch10
Dejun Zhang, Mingbo Hong, Lu Zou, Fei Han et al. • International Journal of Computational Intelligence Systems
Recurrent neural network (RNN) is one of the most popular architectures for addressing variable sequence text, and it shows outstanding results in many natural language processing (NLP) tasks and remarkable performance in capturing long-ter...
DOAJ
Open Access (DOAJ)
DOI: 10.2991/ijcis.d.190710.001
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
Amirsina Torfi, Rouzbeh A. Shirvani, Yaser Keneshloo, Nader Tavaf et al. • arXiv (Cornell University)
(2020)
Natural Language Processing (NLP) helps empower intelligent machines by enhancing a better understanding of the human language for linguistic-based human-computer communication. Recent developments in computational power and the advent of l...
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Open Access
DOI: https://doi.org/10.48550/arxiv.2003.01200
(2019)
The study of the way native human dialects and computer systems interact is known as natural language processing.Cognitive languages require the use of NLP, which has connections to artificial intelligence and computer engineering.In artifi...
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Open Access
DOI: https://doi.org/10.46632/rmc/1/1/014
Alexander F. Gelbukh • International Conference on Hybrid Intelligent Systems (HIS)
(2005)
Summary form only given. Natural language processing (NLP) is a major area of artificial intelligence research, which in its turn serves as a field of application and interaction of a number of other traditional AI areas. Until recently, th...
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DOI: https://doi.org/10.1109/ichis.2005.79
Vineet Raina, Srinath Krishnamurthy • Apress eBooks
(2021)
AI, as discussed in Chapter 1, refers to computers behaving intelligently like humans. One aspect of human intelligence is the capability of understanding and speaking languages. The subfield of AI that focuses on making computers seemingly...
OPENALEX
DOI: https://doi.org/10.1007/978-1-4842-7419-4_6
Dirk Hovy, Shannon Lydia Spruit • Proceedings of the conference - Association for Computational Linguistics. Meeting
(2016)
Medical sciences have long since established an ethics code for experiments, to minimize the risk of harm to subjects.Natural language processing (NLP) used to involve mostly anonymous corpora, with the goal of enriching linguistic analysis...
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Open Access
DOI: https://doi.org/10.18653/v1/p16-2096
(2013)
Welcome to EMNLP 2010, Conference on Empirical Methods in Natural Language Processing! The conference is organized by SIGDAT, the Association for Computational Linguistics' special interest group on linguistic data and corpus-based approach...
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DOI: https://doi.org/10.18653/v1/d13-1
Bohan Li, Yutai Hou, Wanxiang Che • AI Open
(2022)
As an effective strategy, data augmentation (DA) alleviates data scarcity scenarios where deep learning techniques may fail. It is widely applied in computer vision then introduced to natural language processing and achieves improvements in...
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DOI: https://doi.org/10.1016/j.aiopen.2022.03.001
Lei Zhang, Yiru Huang, Leiming Yan, Jinghao Ge et al. • Advanced Intelligent Systems
(2024)
Making computers automatically extract latent scientific knowledge from literature is highly desired for future materials and chemical research in the artificial intelligence era. Herein, the natural language processing (NLP)‐based machine ...
DOAJ
Open Access (DOAJ)
DOI: 10.1002/aisy.202300678
Charaf Ouaddi, Lamya Benaddi, Adnane Souha, Hamza Abdelmalek et al. • IEEE Access
(2025)
Conversational agents are intelligent, ubiquitous software applications widely used across various sectors, such as commerce, tourism, and more. Their key benefits include automating tasks, improving customer service, and ensuring service a...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3574641
C Friedman • PubMed Central
(2000)
Natural language processing systems (NLP) that extract clinical information from textual reports were shown to be effective for limited domains and for particular applications. Because an NLP system typically requires substantial resources ...
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Open Access
PMC: 2243979
Amir A. Kimia, Guergana Savova, Assaf Landschaft, Marvin B. Harper • Pediatric Emergency Care
(2015)
Electronically stored clinical documents may contain both structured data and unstructured data. The use of structured clinical data varies by facility, but clinicians are familiar with coded data such as International Classification of Dis...
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DOI: https://doi.org/10.1097/pec.0000000000000484
Field Cady • Wiley eBooks
(2017)
This chapter starts with several generic sections about natural language processing (NLP) datasets and big-picture concepts. It focuses on the core NLP concepts, and quick-and-dirty techniques to more complicated ones. The most basic concep...
OPENALEX
DOI: https://doi.org/10.1002/9781119092919.ch16
Lingfei Wu, Yu Chen, Kai Shen, Xiaojie Guo et al. • Foundations and Trends® in Machine Learning
(2023)
Deep learning has become the dominant approach in addressing various tasks in Natural Language Processing (NLP). Although text inputs are typically represented as a sequence of tokens, there is a rich variety of NLP problems that can be bes...
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Open Access
DOI: https://doi.org/10.1561/2200000096
Palash Goyal, Sumit Kumar Pandey, Karan Jain • Apress eBooks
(2018)
Discover the concepts of deep learning used for natural language processing (NLP) in this practical book, with full-fledged examples of neural network models such as recurrent neural networks, long short-term memory networks, and sequence-2...
OPENALEX
DOI: https://doi.org/10.1007/978-1-4842-3685-7