Analysis of Genetic Algorithms in Natural Language Processing

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Abstract

Natural language processing (NLP) has increased the interest in genetic algorithm (GA) due to their skills in solving complex optimization problems with extensive research on the use of genetic algorithms in NLP projects has been presented in this paper. First, we present the basic concepts behind genetic algorithms and their relevance to natural language processing. Then, we explore various applications of natural language processing (NLP) that use genetic algorithms, including text classification, sentiment analysis, machine translation, summarization, and question-answering systems. We examine the advantages and disadvantages of genetic algorithm applications in natural language processing by comparing their performance with traditional and modern approaches and discuss the factors influencing their effectiveness. Furthermore, we explore recent advancements, modifications, and hybridizations of Genetic Algorithms tailored to NLP tasks. Finally, we discuss the challenges and future directions in leveraging Genetic Algorithms for enhancing NLP technologies.
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Analysis of Genetic Algorithms in Natural Language Processing | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Short Report Analysis of Genetic Algorithms in Natural Language Processing Ekagrata Bahadur This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3969717/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Natural language processing (NLP) has increased the interest in genetic algorithm (GA) due to their skills in solving complex optimization problems with extensive research on the use of genetic algorithms in NLP projects has been presented in this paper. First, we present the basic concepts behind genetic algorithms and their relevance to natural language processing. Then, we explore various applications of natural language processing (NLP) that use genetic algorithms, including text classification, sentiment analysis, machine translation, summarization, and question-answering systems. We examine the advantages and disadvantages of genetic algorithm applications in natural language processing by comparing their performance with traditional and modern approaches and discuss the factors influencing their effectiveness. Furthermore, we explore recent advancements, modifications, and hybridizations of Genetic Algorithms tailored to NLP tasks. Finally, we discuss the challenges and future directions in leveraging Genetic Algorithms for enhancing NLP technologies. Theoretical Computer Science Artificial Intelligence and Machine Learning Genetic Algorithms Natural Language Processing Optimization Text Classification Sentiment Analysis Machine Translation Summarization Question Answering Systems. Full Text Additional Declarations The authors declare potential competing interests as follows: no Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3969717","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":273649399,"identity":"2188cb52-e47a-4464-9e29-87bb5c4a49c4","order_by":0,"name":"Ekagrata Bahadur","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEElEQVRIiWNgGAWjYDACHihtAGIBkRyIc+ABYS0GcC3GYC0JpGhJbADx8Wnh5zn8+HVFzR95c/azBz+8bbuXPj/s8EOgLXZyug3YtUj2tplZnjlmYLizJy9Zcm5bce7G22kGQC3JxmYHsGsxOM9gZtjAZsC44UCOgTRvW0LuxtkJIC0HErfh0GJ/nv2bYcM/A/sN598Y/wZqSTecnf4BrxYD3h7jh41tBokbbuSYgWxJkJfOwW+LxJkzZYyNfcbJO2e8MbOccy7BcIN0TsGBBAPcfuHvSd/8seGbnO12/hzjG2/KEuTlZ6dv/vChwk4OlxYgYJNAdSpYpQFO5SDA/AGFK9+AV/UoGAWjYBSMQAAAskRkzp4EMSUAAAAASUVORK5CYII=","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Ekagrata","middleName":"","lastName":"Bahadur","suffix":""}],"badges":[],"createdAt":"2024-02-19 10:22:33","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":true,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-3969717/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3969717/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":51344123,"identity":"d3f96434-e4c4-469c-930b-da364db13999","added_by":"auto","created_at":"2024-02-20 01:56:40","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":260522,"visible":true,"origin":"","legend":"","description":"","filename":"AnalysisofGeneticAlgorithminNLP.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3969717/v1_covered_506418d6-42ea-4b83-9a4f-f7b0a3304f7c.pdf"}],"financialInterests":"The authors declare potential competing interests as follows: no","formattedTitle":"\u003cp\u003eAnalysis of Genetic Algorithms in Natural Language Processing\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Amity University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Genetic Algorithms, Natural Language Processing, Optimization, Text Classification, Sentiment Analysis, Machine Translation, Summarization, Question Answering Systems. 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