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Academic Articles & Research Papers
Showing 20 of 1,629 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...
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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...
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DOI: https://doi.org/10.1007/978-1-4842-4131-8_9
Alexander Clark, Chris Fox, Shalom Lappin (2010)
The Handbook of Computational Linguistics and Natural Language Processing provides a comprehensive overview of the concepts, methodologies, and applications being undertaken today in computational linguistics and natural language processing...
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Fontaine-Dussault Z, Hazel L, Dupont L, Jeffrey C et al. • Psychological medicine
(2026)
PMC
PMC Public Access (View-Only)
DOI: 10.1017/S0033291726105662
PMC: PMC13735849
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
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
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
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
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
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
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
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
Yuexiong Ding, Jie Ma, Xiaowei Luo • Automation in Construction
(2022)
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DOI: https://doi.org/10.1016/j.autcon.2022.104169
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
Fangyan Huo, Yihua Li • Discover Artificial Intelligence
(2026)
Abstract This study presents a Data Fusion + Random Forest (RF) framework to predict adult learners’ educational outcomes, such as dropout risk and course completion. Adult lifelong learning is crucial for personal and professional growth, ...
DOAJ
Open Access (DOAJ)
DOI: 10.1007/s44163-026-01962-1
Diksha Khurana, Aditya Koli, Kiran Khatter, Sukhdev Singh • Multimedia Tools and Applications
(2022)
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Open Access
DOI: https://doi.org/10.1007/s11042-022-13428-4
PMC: 9281254
Peter Spyns • Methods of Information in Medicine
(1996)
An overview is given of natural language processing applications in medicine. An attempt has been made to enumerate the most important and known international projects and to summarize their goals, principles, methods and results. A section...
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DOI: https://doi.org/10.1055/s-0038-1634681
Hang Li • National Science Review
(2017)
Deep learning refers to machine learning technologies for learning and utilizing ‘deep’ artificial neural networks, such as deep neural networks (DNN), convolutional neural networks (CNN) and recurrent neural networks (RNN). Recently, deep ...
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DOI: https://doi.org/10.1093/nsr/nwx110
Imed Zitouni • Theory and applications of natural language processing
(2014)
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DOI: https://doi.org/10.1007/978-3-642-45358-8
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