Home / Current Issue / Paper 1704422
The Role of Machine Learning in Natural Language Processing and Computer Vision
Subject area: Science,Engineering and Technology · Area of research: Artificial Intelligence
Abstract
Research and development in artificial intelligence and its associated domains and subfields, such as machine learning, deep learning, and natural language processing, have undergone tremendous growth over the past several years. This increase may be attributed to the rise in popularity of these areas of study. As a result of the availability of a vast diversity of applications and the declining cost of computer systems, researchers have discovered a renewed sensation of excitement in the job that they do. In the modern world, I believe it is fair to state that artificial intelligence and the subfields that fall under its umbrella have been having a favourable impact on a wide variety of business sectors. Machine learning and deep learning not only make companies more efficient, but they have also had a substantial influence on various subfields of artificial intelligence, such as computer vision and natural language processing. Both of these types of learning increase the efficiency of enterprises. Learning techniques have played a very essential part in ensuring that correct analysis is carried out in the field of natural language processing, which refers to the capacity of computers to comprehend human languages. This is a challenging endeavour. In this study, we focus on the significant part that learning strategies play in enhancing the productive capacity of natural language processing.
Keywords
Machine Learning, Deep Learning, Natural Language Processing, Artificial Intelligence.
References
[1] Tatwadarshi P. Nagarhalli, Dr. Vinod Vaze, and Dr. N. K. Rana, “Impact of Machine Learning in NaturalnLanguage Processing: A Review”, Third International Conference on Intelligent Communication TechnologiesandVirtualMobile Networks(ICICV2021),2021.
[2] AravindPai,WhatisTokenizationinNLP?Here’sAllYouNeedToKnow.Availableat:https://www.analyticsvidhya.com/blog/2020/05/what-istokenization-nlp/.
[3] Wahab Khan, Ali Daud, Jamal A. Nasir, Tehmina Amjad," A survey on the state-of-the-art machine learningmodelsinthecontextofNLP",KuwaitJ.Sci.43 (4)pp.95-113,2016.
[4] E.Alpaydın,“IntroductiontoMachineLearning”,2ndEdition,TheMITPress, 2010.
[5] J.Brownlee,“MachineLearningisPopularRightNow”,Availableat:https://machinelearningmastery.com/machinelearning-is-popular/.
[6] P. P. Shinde and S. Shah, “A Review of Machine Learning and Deep Learning Applications”, IEEE FourthInternationalConferenceonComputingCommunicationControlandAutomation(ICCUBEA),2018,pp.1-6.
[7] Edited by Alexander Clark, Chris Fox, and Shalom Lappin, “The Handbook of Computational Linguistics andNaturalLanguageProcessing”,BlackwellPublishingLtd.,2010.
[8] Edited by Alexander Clark, Chris Fox, and Shalom Lappin, “The Handbook of Computational Linguistics andNaturalLanguageProcessing”,BlackwellPublishingLtd., 2010.
[9] Tatwadarshi P. Nagarhalli,Dr. Vinod Vaze,Dr. N. K. Rana,"Impact of Machine Learning in Natural LanguageProcessing: A Review", Proceedings of the Third InternationalConference on Intelligent CommunicationTechnologies and Virtual Mobile Networks (ICICV 2021).IEEE Xplore Part Number: CFP21ONG-ART; 978-0-7381-1183-4.
[10] J. Wu and W. Ma, “A Deep Learning Framework for Coreference Resolution Based on Convolutional NeuralNetwork”,IEEE11thInternationalConferenceonSemantic Computing(ICSC),2017,pp.61-64.
[11] N. Pawar and S. Bhingarkar, “Machine Learning based Sarcasm Detection on Twitter Data”, IEEE 5thInternationalConference onCommunicationand ElectronicsSystems(ICCES),2020,pp.957-961.
[12] Brown,The encyclopedia of language &linguistics.Amsterdam Boston:Elsevier,2006.
[13] G. Pullum, “Philosophy of linguistics,” The Cambridge Companion to History of Philosophy, vol. 2015, 1945.
[14] A.Turing,“Computing machinery and intelligence-am turing” Mind, vol. 59, no. 236, p. 433, 1950.
[15] R. Epstein, Parsing the Turing test: philosophical and methodological issues in the quest for the thinking computer. Dordrecht London: Springer, 2009.
[16] J. Weizenbaum, “Eliza—a computer program for the study of natural language communication between man and machine,” Commun. ACM, vol. 9, no. 1, p. 36–45, Jan. 1966. Available: https://doi.org/10.1145/365153.365168
[17] P. Saygin, I. Cicekli, and V. Akman, Minds and Machines, vol. 10, no. 4, pp. 463–518, 2000. Available: https://doi.org/10.1023/a:1011288000451
[18] “Eugeunegoostman” http://eugenegoostman.elasticbeanstalk.com/
[19] Saenz, “en-USCleverbot Chat Engine Is Learning From The Internet To Talk Like A Human,” Jan. 2010. [Online]. Available: https://singularityhub.com/2010/01/13/cleverbot-chat-engine-is-learning-from-the-internet-to-talk-
[20] L. Von Ahn, M. Blum, N. J. Hopper, and J. Langford, “Captcha: Using hard ai problems for security,” in International conference on the theory and applications of cryptographic techniques. Springer, 2003, pp. 294–311.
[21] C. Manning, “Natural language processing”, in Proceedings of 52nd Annual Meeting of the Association for Computational Linguistics, Citeseer, 2014, pp. 55–60.
[22] Y. Goldberg, “A Primer on Neural Network Models for Natural Language Processing”, Journal of Artificial Intelligence Research, vol. 57, pp. 345–420, Nov. 2016, doi: 10.1613/jair.4992.
[23] T. Young, D. Hazarika, S. Poria and E. Cambria, ”Recent Trends in Deep Learning Based Natural Language Processing [Review Article]”, IEEE Computational Intelligence Magazine, vol. 13, no. 3, pp. 55-75, Aug. 2018, doi: 10.1109/MCI.2018.2840738.
[24] D. W. Otter, J. R. Medina and J. K. Kalita, ”A Survey of the Usages of Deep Learning for Natural Language Processing”, IEEE Transactions on Neural Networks and Learning Systems, vol. 32, no. 2, pp. 604-624, Feb. 2021, doi: 10.1109/TNNLS.2020.2979670.
[25] T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, and J. Dean, “Distributed representations of words and phrases and their compositionality,” Advances in Neural Information Processing Systems, vol. 26, p. 3111–3119, 2013. [Online]. Available: https://papers.nips.cc/paper/2013/hash/9aa42b31882ec039965f3c4923ce901b-Abstract.html
[26] Navaneetha Krishnan Rajagopal, Mankeshva Saini, Rosario Huerta-Soto, Rosa Vílchez-Vásquez, J. N. V. R. Swarup Kumar, Shashi Kant Gupta, Sasikumar Perumal, "Human Resource Demand Prediction and Configuration Model Based on Grey Wolf Optimization and Recurrent Neural Network", Computational Intelligence and Neuroscience, vol. 2022, Article ID 5613407, 11 pages, 2022. https://doi.org/10.1155/2022/5613407
[27] Navaneetha Krishnan Rajagopal, Naila Iqbal Qureshi, S. Durga, Edwin Hernan Ramirez Asis, Rosario Mercedes Huerta Soto, Shashi Kant Gupta, S. Deepak, "Future of Business Culture: An Artificial Intelligence-Driven Digital Framework for Organization Decision-Making Process", Complexity, vol. 2022, Article ID 7796507, 14 pages, 2022. https://doi.org/10.1155/2022/7796507
[28] EshragRefaee, Shabana Parveen, Khan Mohamed Jarina Begum, Fatima Parveen, M. Chithik Raja, Shashi Kant Gupta, Santhosh Krishnan, "Secure and Scalable Healthcare Data Transmission in IoT Based on Optimized Routing Protocols for Mobile Computing Applications", Wireless Communications and Mobile Computing, vol. 2022, Article ID 5665408, 12 pages, 2022. https://doi.org/10.1155/2022/5665408
[29] Rajesh Kumar Kaushal, Rajat Bhardwaj, Naveen Kumar, Abeer A. Aljohani, Shashi Kant Gupta, Prabhdeep Singh, Nitin Purohit, "Using Mobile Computing to Provide a Smart and Secure Internet of Things (IoT) Framework for Medical Applications", Wireless Communications and Mobile Computing, vol. 2022, Article ID 8741357, 13 pages, 2022. https://doi.org/10.1155/2022/8741357
[30] BramahHazela et al 2022 ECS Trans. 107 2651 https://doi.org/10.1149/10701.2651ecst
[31] Ashish Kumar Pandey et al 2022 ECS Trans. 107 2681 https://doi.org/10.1149/10701.2681ecst
[32] G. S. Jayesh et al 2022 ECS Trans. 107 2715 https://doi.org/10.1149/10701.2715ecst
[33] Shashi Kant Gupta et al 2022 ECS Trans. 107 2927 https://doi.org/10.1149/10701.2927ecst
[34] S. Saxena, D. Yagyasen, C. N. Saranya, R. S. K. Boddu, A. K. Sharma and S. K. Gupta, "Hybrid Cloud Computing for Data Security System," 2021 International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA), 2021, pp. 1-8, doi: 10.1109/ICAECA52838.2021.9675493.
[35] S. K. Gupta, B. Pattnaik, V. Agrawal, R. S. K. Boddu, A. Srivastava and B. Hazela, "Malware Detection Using Genetic Cascaded Support Vector Machine Classifier in Internet of Things," 2022 Second International Conference on Computer Science, Engineering and Applications (ICCSEA), 2022, pp. 1-6, doi: 10.1109/ICCSEA54677.2022.9936404.
[36] Natarajan, R.; Lokesh, G.H.; Flammini, F.; Premkumar, A.; Venkatesan, V.K.; Gupta, S.K. A Novel Framework on Security and Energy Enhancement Based on Internet of Medical Things for Healthcare 5.0. Infrastructures2023, 8, 22. https://doi.org/10.3390/infrastructures8020022
[37] V. S. Kumar, A. Alemran, D. A. Karras, S. Kant Gupta, C. Kumar Dixit and B. Haralayya, "Natural Language Processing using Graph Neural Network for Text Classification," 2022 International Conference on Knowledge Engineering and Communication Systems (ICKES), Chickballapur, India, 2022, pp. 1-5, doi: 10.1109/ICKECS56523.2022.10060655.
[38] M. Sakthivel, S. Kant Gupta, D. A. Karras, A. Khang, C. Kumar Dixit and B. Haralayya, "Solving Vehicle Routing Problem for Intelligent Systems using Delaunay Triangulation," 2022 International Conference on Knowledge Engineering and Communication Systems (ICKES), Chickballapur, India, 2022, pp. 1-5, doi: 10.1109/ICKECS56523.2022.10060807.
[39] S. Tahilyani, S. Saxena, D. A. Karras, S. Kant Gupta, C. Kumar Dixit and B. Haralayya, "Deployment of Autonomous Vehicles in Agricultural and using Voronoi Partitioning," 2022 International Conference on Knowledge Engineering and Communication Systems (ICKES), Chickballapur, India, 2022, pp. 1-5, doi: 10.1109/ICKECS56523.2022.10060773.
[40] V. S. Kumar, A. Alemran, S. K. Gupta, B. Hazela, C. K. Dixit and B. Haralayya, "Extraction of SIFT Features for Identifying Disaster Hit areas using Machine Learning Techniques," 2022 International Conference on Knowledge Engineering and Communication Systems (ICKES), Chickballapur, India, 2022, pp. 1-5, doi: 10.1109/ICKECS56523.2022.10060037.
[41] V. S. Kumar, M. Sakthivel, D. A. Karras, S. Kant Gupta, S. M. Parambil Gangadharan and B. Haralayya, "Drone Surveillance in Flood Affected Areas using Firefly Algorithm," 2022 International Conference on Knowledge Engineering and Communication Systems (ICKES), Chickballapur, India, 2022, pp. 1-5, doi: 10.1109/ICKECS56523.2022.10060857.
[42] Parin Somani, Sunil Kumar Vohra, Subrata Chowdhury, Shashi Kant Gupta. "Implementation of a Blockchain-based Smart Shopping System for Automated Bill Generation Using Smart Carts with Cryptographic Algorithms." CRC Press, 2022. https://doi.org/10.1201/9781003269281-11.
[43] Shivlal Mewada, Dhruva Sreenivasa Chakravarthi, S. J. Sultanuddin, Shashi Kant Gupta. "Design and Implementation of a Smart Healthcare System Using Blockchain Technology with A Dragonfly Optimization-based Blowfish Encryption Algorithm." CRC Press, 2022. https://doi.org/10.1201/9781003269281-10.
[44] Ahmed Muayad Younus, Mohanad S.S. Abumandil, Veer P. Gangwar, Shashi Kant Gupta. " AI-Based Smart Education System for a Smart City Using an Improved Self-Adaptive Leap-Frogging Algorithm." CRC Press, 2022. https://doi.org/10.1201/9781003252542-14.
[45] Rosak-Szyrocka, J., Żywiołek, J., & Shahbaz, M. (Eds.). (2023). Quality Management, Value Creation and the Digital Economy (1st ed.). Routledge. https://doi.org/10.4324/9781003404682
[46] Dr. Shashi Kant Gupta, Hayath T M., Lack of it Infrastructure for ICT Based Education as an Emerging Issue in Online Education, TTAICTE. 2022 July; 1(3): 19-24. Published online 2022 July, doi.org/10.36647/TTAICTE/01.03.A004
[47] Hayath T M., Dr. Shashi Kant Gupta, Pedagogical Principles in Learning and Its Impact on Enhancing Motivation of Students, TTAICTE. 2022 October; 1(2): 19-24. Published online 2022 July, doi.org/10.36647/TTAICTE/01.04.A004
[48] Shaily Malik, Dr. Shashi Kant Gupta, “The Importance of Text Mining for Services Management”, TTIDMKD. 2022 November; 2(4): 28-33. Published online 2022 November doi.org/10.36647/TTIDMKD/02.04.A006
[49] Dr. Shashi Kant Gupta, Shaily Malik, “Application of Predictive Analytics in Agriculture”, TTIDMKD. 2022 November; 2(4): 1-5. Published online 2022 November doi.org/10.36647/TTIDMKD/02.04.A001
[50] Dr. Shashi Kant Gupta, Budi Artono, “Bioengineering in the Development of Artificial Hips, Knees, and other joints. Ultrasound, MRI, and other Medical Imaging Techniques”, TTIRAS. 2022 June; 2(2): 10–15. Published online 2022 June doi.org/10.36647/TTIRAS/02.02.A002
[51] Dr. Shashi Kant Gupta, Dr. A. S. A. Ferdous Alam, “Concept of E Business Standardization and its Overall Process” TJAEE 2022 August; 1(3): 1–8. Published online 2022 August
How to cite this paper
@article{1704422,
author = {Adheer Arun Goyal},
title = {The Role of Machine Learning in Natural Language Processing and Computer Vision},
journal = {Iconic Research And Engineering Journals},
year = {2023},
volume = {6},
number = {11},
pages = {185-195},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1704422.pdf},
abstract = {Research and development in artificial intelligence and its associated domains and subfields, such as machine learning, deep learning, and natural language processing, have undergone tremendous growth over the past several years. This increase may be attributed to the rise in popularity of these areas of study. As a result of the availability of a vast diversity of applications and the declining cost of computer systems, researchers have discovered a renewed sensation of excitement in the job that they do. In the modern world, I believe it is fair to state that artificial intelligence and the subfields that fall under its umbrella have been having a favourable impact on a wide variety of business sectors. Machine learning and deep learning not only make companies more efficient, but they have also had a substantial influence on various subfields of artificial intelligence, such as computer vision and natural language processing. Both of these types of learning increase the efficiency of enterprises. Learning techniques have played a very essential part in ensuring that correct analysis is carried out in the field of natural language processing, which refers to the capacity of computers to comprehend human languages. This is a challenging endeavour. In this study, we focus on the significant part that learning strategies play in enhancing the productive capacity of natural language processing.},
keywords = {Machine Learning, Deep Learning, Natural Language Processing, Artificial Intelligence.},
month = {May},
}