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Journal articles on the topic 'Natural Language Processing'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Patel, Stuti. "Natural Language Processing." International Journal of Science and Research (IJSR) 12, no. 2 (2023): 1123–29. http://dx.doi.org/10.21275/sr23216193027.

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Lone, Nawaz Ali, Kaiser J. Giri, and Rumaan Bashir. "Natural Language Processing Resources for the Kashmiri Language." Indian Journal Of Science And Technology 15, no. 43 (2022): 2275–81. http://dx.doi.org/10.17485/ijst/v15i43.1964.

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3

Kumar, Deepak, Dr Amandeep, Pinki Pinki, et al. "Visualization by Natural Language Processing and Large Language Model." International Journal of Research Publication and Reviews 6, no. 6 (2025): 11225–31. https://doi.org/10.55248/gengpi.6.0625.2340.

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4

Niimi, Akio. "Natural Language Processing." Chest 159, no. 6 (2021): 2149–50. http://dx.doi.org/10.1016/j.chest.2021.01.045.

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5

HASHIDA, KOICHI. "Natural Language Processing." Journal of the Institute of Electrical Engineers of Japan 121, no. 3 (2001): 195–98. http://dx.doi.org/10.1541/ieejjournal.121.195.

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6

N. O. Sadiku, Matthew, Yu Zhou, and Sarhan M. Musa. "Natural Language Processing." International Journal of Advances in Scientific Research and Engineering 4, no. 5 (2018): 68–70. http://dx.doi.org/10.31695/ijasre.2018.32708.

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7

Covington, Michael A., Fernando C. N. Pereira, and Barbara J. Grosz. "Natural Language Processing." Language 71, no. 3 (1995): 652. http://dx.doi.org/10.2307/416262.

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8

Jain, Aditya, Gandhar Kulkarni, and Vraj Shah. "Natural Language Processing." International Journal of Computer Sciences and Engineering 6, no. 1 (2018): 161–67. http://dx.doi.org/10.26438/ijcse/v6i1.161167.

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9

Yilmaz, A. Egemen. "Natural Language Processing." International Journal of Systems and Service-Oriented Engineering 4, no. 1 (2014): 68–83. http://dx.doi.org/10.4018/ijssoe.2014010105.

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Requirement analysis is the very first and crucial step in the software development processes. On the other hand, as previously addressed by other researchers, it is the Achilles' heel of the whole process since the requirements lie on the problem space, whereas other software artifacts are on the solution space. Stating the requirements in a clear manner eases the following steps in the process as well as reducing the number of potential errors. In this paper, techniques for the improvement of the requirements expressed in the natural language are revisited. These techniques try to check the

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10

Weischedel, R., J. Carbonell, B. Grosz, et al. "Natural Language Processing." Annual Review of Computer Science 4, no. 1 (1990): 435–52. http://dx.doi.org/10.1146/annurev.cs.04.060190.002251.

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11

Wilks, Yorick. "Natural language processing." Communications of the ACM 39, no. 1 (1996): 60–62. http://dx.doi.org/10.1145/234173.234180.

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12

Patten, T., and P. Jacobs. "Natural-language processing." IEEE Expert 9, no. 1 (1994): 35. http://dx.doi.org/10.1109/64.295134.

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13

Rindflesch, Thomas C. "Natural Language Processing." Annual Review of Applied Linguistics 16 (March 1996): 70–85. http://dx.doi.org/10.1017/s0267190500001446.

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Work in computational linguistics began very soon after the development of the first computers (Booth, Brandwood and Cleave 1958), yet in the intervening four decades there has been a pervasive feeling that progress in computer understanding of natural language has not been commensurate with progress in other computer applications. Recently, a number of prominent researchers in natural language processing met to assess the state of the discipline and discuss future directions (Bates and Weischedel 1993). The consensus of this meeting was that increased attention to large amounts of lexical and

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14

Heidorn, P. Bryan. "Natural language processing." Information Processing & Management 32, no. 1 (1996): 122–23. http://dx.doi.org/10.1016/s0306-4573(96)90089-8.

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15

Selfridge, Mallory. "Natural language processing." Artificial Intelligence in Engineering 2, no. 1 (1987): 50. http://dx.doi.org/10.1016/0954-1810(87)90076-8.

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16

JOSHI, A. K. "Natural Language Processing." Science 253, no. 5025 (1991): 1242–49. http://dx.doi.org/10.1126/science.253.5025.1242.

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17

Grosz, Barbara J. "Natural-language processing." Artificial Intelligence 25, no. 1 (1985): 1–4. http://dx.doi.org/10.1016/0004-3702(85)90038-4.

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18

Horacek, Helmut. "Natural language processing." Computer Physics Communications 61, no. 1-2 (1990): 76–92. http://dx.doi.org/10.1016/0010-4655(90)90107-c.

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19

Chowdhury, Gobinda G. "Natural language processing." Annual Review of Information Science and Technology 37, no. 1 (2005): 51–89. http://dx.doi.org/10.1002/aris.1440370103.

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20

Hirschberg, Julia, Bruce W. Ballard, and Donald Hindle. "Natural Language Processing." AT&T Technical Journal 67, no. 1 (1988): 41–57. http://dx.doi.org/10.1002/j.1538-7305.1988.tb00232.x.

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21

Chandrasekaran, Arvind. "Natural Language Processing." International Journal on Cybernetics & Informatics 12, no. 2 (2023): 57–61. http://dx.doi.org/10.5121/ijci.2023.120205.

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Hints of the outbreak are detected through the modified circumstances favoring the outbreaks, like the warm weather contributing to epidermal outbreaks or the loss of sanitation leading to cholera outbreaks typically relying on the routine reports from the healthcare facilities, secondary data like attendance monitoring at workplaces and schools, the web, and the media play a significant informational source with more than 60% of the initial outbreak reporting to the informal sources. Through the application of natural language processing methods and machine learning technologies, a pipeline i

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22

Németh, Renáta, and Júlia Koltai. "Natural language processing." Intersections 9, no. 1 (2023): 5–22. http://dx.doi.org/10.17356/ieejsp.v9i1.871.

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Natural language processing (NLP) methods are designed to automatically process and analyze large amounts of textual data. The integration of this new-generation toolbox into sociology faces many challenges. NLP was institutionalized outside of sociology, while the expertise of sociology has been based on its own methods of research. Another challenge is epistemological: it is related to the validity of digital data and the different viewpoints associated with predictive and causal approaches. In our paper, we discuss the challenges and opportunities of the use of NLP in sociology, offer some

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23

Martinez, Angel R. "Natural language processing." Wiley Interdisciplinary Reviews: Computational Statistics 2, no. 3 (2010): 352–57. http://dx.doi.org/10.1002/wics.76.

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24

Marcus, M. "New trends in natural language processing: statistical natural language processing." Proceedings of the National Academy of Sciences 92, no. 22 (1995): 10052–59. http://dx.doi.org/10.1073/pnas.92.22.10052.

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25

Vilson, Minu Mariya, Menon Bhavana Rajan, and Mrs Ann Rija Paul. "Motion of curtains using Natural Language Processing." International Journal of Trend in Scientific Research and Development Volume-3, Issue-3 (2019): 1840–43. http://dx.doi.org/10.31142/ijtsrd23199.

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26

Maitra, Arunima. "Natural Language Processing in Court Order Scrutiny." International Journal of Science and Research (IJSR) 11, no. 11 (2022): 1176–80. http://dx.doi.org/10.21275/sr221121200156.

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27

Shamsitdinova, M. "Incorporating Natural Language Processing Technologies for Personalized Language Learning Experience." International Journal of Law And Criminology 5, no. 5 (2025): 79–80. https://doi.org/10.37547/ijlc/volume05issue05-11.

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This paper explores the application of Natural Language Processing (NLP) technologies in delivering personalized language learning experiences. As language learning evolves with digital transformation, NLP stands out as a powerful tool for customizing content, automating feedback, and enhancing learner engagement. The study discusses current NLP techniques, their integration into language education platforms, and the pedagogical benefits of adaptive learning systems. It concludes with challenges and future prospects of implementing NLP in educational settings.

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28

Chikkarangaiah, Jayanth, Adarsh Uday, David De Hilster, Shobha Gangadhar, and Jyoti Shetty. "Enhancing the English natural language processing dictionary using natural language processing++." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 3 (2024): 3466. http://dx.doi.org/10.11591/ijai.v13.i3.pp3466-3477.

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<p><span lang="EN-US">Every natural language-based project requires the use of an English dictionary. But the current English dictionaries are not updated as the English language is constantly evolving. The English dictionary used for natural language processing (NLP) projects needs to be enhanced by adding more words and phrases. This helps in improving the accuracy of NLP applications such as machine translation, performance of text analysis, recognition, and part of speech (POS) tagging. Several approaches are proposed in this direction, this paper develops and demonstrates enha

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29

Jayanth, Chikkarangaiah, Uday Adarsh, De Hilster David, Gangadhar Shobha, and Shetty Jyoti. "Enhancing the English natural language processing dictionary using natural language processing++." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 3 (2024): 3466–77. https://doi.org/10.11591/ijai.v13.i3.pp3466-3477.

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Every natural language-based project requires the use of an English dictionary. But the current English dictionaries are not updated as the English language is constantly evolving. The English dictionary used for natural language processing (NLP) projects needs to be enhanced by adding more words and phrases. This helps in improving the accuracy of NLP applications such as machine translation, performance of text analysis, recognition, and part of speech (POS) tagging. Several approaches are proposed in this direction, this paper develops and demonstrates enhancement of the English dictionary

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30

Ali, Miss Aliya Anam Shoukat. "AI-Natural Language Processing (NLP)." International Journal for Research in Applied Science and Engineering Technology 9, no. VIII (2021): 135–40. http://dx.doi.org/10.22214/ijraset.2021.37293.

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Natural Language Processing (NLP) could be a branch of Artificial Intelligence (AI) that allows machines to know the human language. Its goal is to form systems that can make sense of text and automatically perform tasks like translation, spell check, or topic classification. Natural language processing (NLP) has recently gained much attention for representing and analysing human language computationally. It's spread its applications in various fields like computational linguistics, email spam detection, information extraction, summarization, medical, and question answering etc. The goal of th

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31

Sawant, Isha Sudhir. "Natural Language Processing (NLP) from Image to Text." International Journal of Research Publication and Reviews 5, no. 5 (2024): 13103–9. http://dx.doi.org/10.55248/gengpi.5.0524.1463.

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32

Søgaard, Anders. "Explainable Natural Language Processing." Synthesis Lectures on Human Language Technologies 14, no. 3 (2021): 1–123. http://dx.doi.org/10.2200/s01118ed1v01y202107hlt051.

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33

Salt, Jessica, Polina Harik, and Michael A. Barone. "Leveraging Natural Language Processing." Academic Medicine 94, no. 3 (2019): 314–16. http://dx.doi.org/10.1097/acm.0000000000002558.

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34

Farghaly, Ali, and Khaled Shaalan. "Arabic Natural Language Processing." ACM Transactions on Asian Language Information Processing 8, no. 4 (2009): 1–22. http://dx.doi.org/10.1145/1644879.1644881.

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35

Grefenstette, Gregory, and Frédérique Segond. "Multilingual Natural Language Processing." International Journal of Corpus Linguistics 2, no. 1 (1997): 153–62. http://dx.doi.org/10.1075/ijcl.2.1.08gre.

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36

Kim, Jin-Dong. "Biomedical Natural Language Processing." Computational Linguistics 43, no. 1 (2017): 265–67. http://dx.doi.org/10.1162/coli_r_00281.

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37

Raval, Abhilasha, and Kashyp Dave. "Natural Language Processing- AI." INTERNATIONAL JOURNAL OF ADVANCE RESEARCH IN COMPUTER SCIENCE AND MANAGEMENT STUDIES 11, no. 7 (2023): 20–23. http://dx.doi.org/10.61161/ijarcsms.v11i7.5.

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38

G, Dr Chandrika. "Natural Language Processing (NLP)." International Journal for Research in Applied Science and Engineering Technology 12, no. 6 (2024): 1092–95. http://dx.doi.org/10.22214/ijraset.2024.63281.

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Abstract: Machines utilize Natural Language Processing (NLP), a subfield of Artificial Intelligence (AI), to comprehend, evaluate, and translate human languages. Due to advancements in information and communication technology over the last ten years, NLP has gained increased awareness and has been the subject of several studies. Understanding the steps required to advance literary understanding is so crucial. The study's objective is to provide an organized review of the literature in NLP research using bibliometric analysis. In the discipline of NLP, the study highlights important research fi

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39

Cunliffe, Daniel, Andreas Vlachidis, Daniel Williams, and Douglas Tudhope. "Natural language processing for under-resourced languages: Developing a Welsh natural language toolkit." Computer Speech & Language 72 (March 2022): 101311. http://dx.doi.org/10.1016/j.csl.2021.101311.

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40

Moaiad, Yazeed Al, Mohammad Alobed, Mahmoud Alsakhnini, and Alaa M. Momani. "Challenges in natural Arabic language processing." Edelweiss Applied Science and Technology 8, no. 6 (2024): 4700–4705. http://dx.doi.org/10.55214/25768484.v8i6.3018.

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Speech recognition and text summarization, plagiarism detection, machine translation, chatbots, sentiment analysis (SA), question answering (QA), and dialogue systems are all products of natural language processing (NLP), a branch of AI concerned with modeling natural languages for the purpose of developing relevant applications. NLP draws on several disciplines, not only computer science and linguistics, for its research and development. These include cognitive science, psychology, mathematics, and more. More than 1.5 billion Muslims throughout the world depend on the Arabic language for thei

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41

Dudaš, Adam, and Jarmila Skrinarova. "Natural Language Processing in Translation of Relational Languages." IPSI Transactions on Internet Research 19, no. 01 (2023): 17–23. http://dx.doi.org/10.58245/ipsi.tir.2301.04.

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Methods of data manipulation in combination with sturcture of the data and integrity constraints define data model used in the relational databases. This article focuses on the methods and processes of operation sets which are used for selection of data from relational database and translation between various formats of this manipulation. The article presents the design, implementation and experimental evaluation of tool for translating between relational algebra, tuple relational calculus, Structured Query Language and unrestricted natural language in all directions. Presented software tool t

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42

Pakray, Partha, Alexander Gelbukh, and Sivaji Bandyopadhyay. "Natural language processing applications for low-resource languages." Natural Language Processing 31, no. 2 (2025): 183–97. https://doi.org/10.1017/nlp.2024.33.

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AbstractNatural language processing (NLP) has significantly advanced our ability to model and interact with human language through technology. However, these advancements have disproportionately benefited high-resource languages with abundant data for training complex models. Low-resource languages, often spoken by smaller or marginalized communities, need help realizing the full potential of NLP applications. The primary challenges in developing NLP applications for low-resource languages stem from the need for large, well-annotated datasets, standardized tools, and linguistic resources. This

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43

Nawaz, Ali Lone, J. Giri Kaiser, and Bashir Rumaan. "Natural Language Processing Resources for the Kashmiri Language." Indian Journal of Science and Technology 15, no. 43 (2022): 2275–81. https://doi.org/10.17485/IJST/v15i43.1964.

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Abstract <strong>Objectives:</strong> The main objective of this paper as a maiden attempt is to identify the basic resources necessary for undertaking Natural Language Processing (NLP) specific research activities pertaining to Kashmiri language. The paper also deliberates on key issues related to Natural Language Processing of Kashmiri language such as complex linguistic phenomena, the lack of standard linguistic tools, documented as well as standardized resources and the influence of some dominant languages mostly Urdu and English on Kashmiri language. <strong>Methods:</strong>&nb

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44

S Kapse, Vaishali, and Sonal S Deshmukh. "Study of Marathi Text Summarization using Natural Language Processing." International Journal of Science and Research (IJSR) 14, no. 3 (2025): 1004–9. https://doi.org/10.21275/sr25321000100.

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45

Minhwa Chung and D. Moldevan. "Applying parallel processing to natural-language processing." IEEE Expert 9, no. 1 (1994): 36–44. http://dx.doi.org/10.1109/64.295133.

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46

G, Sajini. "Computational Evaluation of Language Models by Considering Various Scaling Properties for Processing Natural Languages." Journal of Advanced Research in Dynamical and Control Systems 12, SP7 (2020): 691–700. http://dx.doi.org/10.5373/jardcs/v12sp7/20202159.

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47

IKEDA, Takashi, and Tadahiro MATSUMOTO. "Braille, Sign Language and Natural Language Processing." IEICE ESS FUNDAMENTALS REVIEW 4, no. 4 (2011): 282–92. http://dx.doi.org/10.1587/essfr.4.282.

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48

Ward, R. D. "Natural Language Processing and the Language‐Impaired." PLET: Programmed Learning & Educational Technology 23, no. 2 (1986): 144–49. http://dx.doi.org/10.1080/0033039860230208.

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49

Sharma, Sapna. "Natural Language Processing in AI: Language Interpreter." Journal of Artificial Intelligence Research & Advances 7, no. 2 (2020): 21–27. http://dx.doi.org/10.37591/joaira.v7i2.2538.

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50

Rohit Kumar Yadav, Aanchal Madaan, and Janu. "Comprehensive analysis of natural language processing." Global Journal of Engineering and Technology Advances 19, no. 1 (2024): 083–90. http://dx.doi.org/10.30574/gjeta.2024.19.1.0058.

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Natural Language Processing (NLP) is a fascinating field of study that teaches computers to understand and use human language. This means that computers can read, write, and even translate text just like humans. NLP has many practical uses, such as categorizing text, identifying the tone of language, recognizing names in text, translating languages, and answering questions. NLP has come a long way since it was first developed. In the past, it relied on strict rules to understand language, but now it uses advanced techniques like machine learning and deep learning to understand text. However, t

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