Natural Language Processing In Artificial Intelligence
NATURAL LANGUAGE PROCESSINGIN ARTIFICIAL INTELLIGENCE
NATURAL LANGUAGE PROCESSINGIN ARTIFICIAL INTELLIGENCEEdited byBrojo Kishore Mishra, PhDRaghvendra Kumar, PhD
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If any copyright material has not been acknowledged, pleasewrite and let us know so we may rectify in any future reprint.Trademark Notice: Registered trademark of products or corporate names are used only for explanation and identificationwithout intent to infringe.Library and Archives Canada Cataloguing in PublicationTitle: Natural language processing in artificial intelligence / edited by Brojo Kishore Mishra, PhD, Raghvendra Kumar,PhD.Names: Mishra, Brojo Kishore, 1979- editor. Kumar, Raghvendra, 1987- editor.Description: Includes bibliographical references and index.Identifiers: Canadiana (print) 20200224727 Canadiana (ebook) 20200224816 ISBN 9781771888646 (hardcover) ISBN 9780367808495 (ebook)Subjects: LCSH: Natural language processing (Computer science) LCSH: Artificial intelligence.Classification: LCC QA76.9.N38 N38 2020 DDC 006.3/5—dc23Library of Congress Cataloging-in-Publication DataNames: Mishra, Brojo Kishore, 1979- editor. Kumar, Raghvendra, 1987- editor.Title: Natural language processing in Artificial Intelligence / edited by Brojo Kishore Mishra, PhD., Raghvendra Kumar,PhD.Description: Burlington, ON, Canada ; Palm Bay, Florida : Apple Academic Press, 2020. Includes bibliographicalreferences and index. Summary: “This volume, Natural Language Processing in Artificial Intelligence, focuses onnatural language processing (NLP), artificial intelligence (AI), and allied areas. The book delves into natural languageprocessing, which enables communication between people and computers and automatic translation to facilitate easyinteraction with others around the world. It discusses theoretical work and advanced applications, approaches, andtechniques for computational models of information and how it presented by language (artificial, human, or naturalin other ways). It looks at intelligent natural language processing and related models of thought, mental states,reasoning, and other cognitive processes. It explores the difficult problems and challenges related to partiality, underspecification, and context-dependency, which are signature features of information in nature and natural languages.Key features: Addresses the functional frameworks and workflow that are trending in NLP and AI Explores basic andhigh level concepts, thus serving as a resource for those in the industry while also helping beginners to understandboth basic and advanced aspects Looks at the latest technologies and the major challenges, issues, and advances inNLP and AI Explores an intelligent field monitoring and automated system through AI with NLP and its implicationsfor the real world Discusses data acquisition and presents a real-time case study with illustrations related to dataintensive technologies in AI and NLP Topics include the process of business intelligence and how this platformis used, the concepts of Information retrieval systems, the neural machine translation (NMT) process, the choiceof words and text in natural language processing, embedded traffic control and management systems, a techniquefor generating ontology by adopting the fruit fly optimization algorithm, POS labeling using the Viterbi algorithm,how natural language processing techniques can be used to prevent phishing attacks, and more. This volume willbe a useful and informative resource for faculty, advanced-level students, and professionals in the field of artificialintelligence, natural language processing, and other areas”-- Provided by publisher.Identifiers: LCCN 2020016543 (print) LCCN 2020016544 (ebook) ISBN 9781771888646 (hardcover) ISBN 9780367808495 (ebook)Subjects: LCSH: Natural language processing (Computer science)Classification: LCC QA76.9.N38 N3846 2020 (print) LCC QA76.9.N38 (ebook) DDC 006.3/5--dc23LC record available at https://lccn.loc.gov/2020016543LC ebook record available at https://lccn.loc.gov/2020016544Apple Academic Press also publishes its books in a variety of electronic formats. Some content that appears in print may not beavailable in electronic format. For information about Apple Academic Press products, visit our website at www.appleacademicpress.com and the CRC Press website at www.crcpress.com
About the EditorsBrojo Kishore Mishra, PhDProfessor, Department of Computer Science and Engineering,GIET University, Gunupur, Odisha, IndiaBrojo Kishore Mishra, PhD, is a Professor in the Computer Scienceand Engineering Department at the Gandhi Institute of Engineering andTechnology University (GIET), Gunupur, Odisha, India. He has publishedmore than 30 research papers in national and international conferenceproceedings, over 25 research papers in peer-reviewed journals, and over22 book chapters, and has authored two books and edited three books todate. His research interests include data mining and big data analysis,machine learning, soft computing, and evolutionary computation. Hereceived his PhD degree in Computer Science from the BerhampurUniversity, Brahmapur, Odisha, India.Raghvendra Kumar, PhDAssociate Professor, Computer Science & Engineering Department,GIET University, Gunupur, Odisha, IndiaRaghvendra Kumar, PhD, is an Associate Professor in the Computer Scienceand Engineering Department at the Gandhi Institute of Engineering andTechnology University (GIET), Gunupur, Odisha, India. He also serves asDirector of the IT and Data Science Department at the Vietnam Center ofResearch in Economics, Management, Environment, Hanoi, Viet Nam. Dr.Kumar serves as Editor of the book series Internet of Everything: Security andPrivacy Paradigm (CRC Press/Taylor & Francis Group) and the book seriesBiomedical Engineering: Techniques and Applications (Apple AcademicPress). He has published a number of research papers in international journalsand conferences. He has served in many roles for international and nationalconferences, including organizing chair for several conferences, volumeeditor, volume editor, keynote speaker, session chair or co-chair, publicitychair, publication chair, advisory board member, and technical programcommittee member. He has also served as a guest editor for many specialissues of reputed journals. He authored and edited 17 computer science books
viAbout the Editorsin field of internet of things, data mining, biomedical engineering, big data,robotics, graph theory, and Turing machines. He is the Managing Editor ofthe International Journal of Machine Learning and Networked CollaborativeEngineering. He received a best paper award at the IEEE Conference 2013and Young Achiever Award–2016 by IEAE Association for his research workin the field of distributed database. His research areas are computer sciencecloud computing, big data and database, security and privacy, multimediasystem, machine learning, computational Intelligence, and image processing.Dr. Kumar received his BTech in Computer Science and Engineering fromSRM University Chennai (Tamil Nadu), India, his MTech in ComputerScience and Engineering from KIIT University, Bhubaneswar, (Odisha)India, and his PhD in Computer Science and Engineering from JodhpurNational University, Jodhpur (Rajasthan), India.
ContentsContributors. ixAbbreviations . xiPreface .xv1.A Survey on Social Business Intelligence: A Case Study ofApplication of Dynamic Social Networks for Decision Making . 1Subrata Paul, Chandan Koner, and Anirban Mitra2.Critical Concepts and Techniques for InformationRetrieval System. 29Mohd Shahid Husain3.Futurity of Translation Algorithms for Neural MachineTranslation (NMT) and Its Vision . 53K. Mandal, G. S. Pradeep Ghantasala, Firoz Khan, R. Sathiyaraj, and B. Balamurugan4.Role of Machine Learning and Application TowardsInformation Retrieval in Cloud . 97Mishra Sambit Kumar, Mishra Brojo Kishore, and Prasad Suman Sourav5.Ontology-Based Information Retrieval and Matching inIoT Applications . 113M. Lawanya Shri, E. Ganga Devi, Balamurugan Balusamy, and Jyotir Moy Chatterjee6.Parts-of-Speech Tagging in NLP: Utility, Types, andSome Popular POS Taggers . 131Soumitra Ghosh and Brojo Kishore Mishra7.Text Mining. 167S. Karthikeyan, Jeevanandam Jotheeswaran, B. Balamurugan, andJyotir Moy Chatterjee8.A Brief Overview of Natural Language Processing andArtificial Intelligence . 211Sushree Bibhuprada B. Priyadarshini, Amiya Bhusan Bagjadab, andBrojo Kishore Mishra
Contentsviii9.Use of Machine Learning and a Natural Language ProcessingApproach for Detecting Phishing Attacks . 225Chandrakanta Mahanty, Devpriya Panda, and Brojo Kishore Mishra10. Role of Computational Intelligence in NaturalLanguage Processing. 253Bishwa Ranjan Das and Brojo Kishore MishraIndex . 269
ContributorsAmiya Bhusan BagjadabSambalpur University of Information Technology, Burla, India, E-mail: amiya7bhusan7@gmail.comB. BalamuruganProfessor, School of Computing Science and Engineering, Galgotias University, Greater Noida,Uttar Pradesh, India, E-mail: kadavulai@gmail.comBalamurugan BalusamySchool of Computer Science and Engineering, Galgotias University, Noida, Uttar Pradesh, IndiaJyotir Moy ChatterjeeSchool of Computing Science and Engineering, Department of IT, LBEF (APUTI), Kathmandu,Nepal, E-mail: jyotirm4@gmail.comBishwa Ranjan DasNorth Orissa University, Baripada, India, E-mail: biswadas.bulu@gmail.comE. Ganga DeviLoyola College, Chennai, Tamil Nadu, IndiaG. S. Pradeep GhantasalaProfessor, Department of Computer Science and Engineering, Malla Reddy Institute of Technologyand Science, Hyderabad, Telengana, India, E-mail: ggspradeep@gmail.comSoumitra GhoshDepartment of Computer Science and Engineering, Indian Institute of Technology Patna, IndiaMohd Shahid HusainAssistant Professor, Information Technology Department, College of Applied Sciences, Ibri,Ministry of Higher Education, Oman, Tel.: 968-94714261, E-mails: anandam JotheeswaranSchool of Computing Science and Engineering, Galgotias University, Greater Noida, Uttar Pradesh,India, E-mail: jeevanandamj@gmail.comS. KarthikeyanSchool of Computing Science and Engineering, Galgotias University, Greater Noida, Uttar Pradesh,India, E-mail: link2karthikcse@gmail.comFiroz KhanProfessor, IT Faculty, Dubai Mens College, Higher Colleges of Technology, UAE,E-mail: fk7@hotmail.comMishra Brojo KishoreDepartment of Computer Science and Engineering, GIET University, Gunupur, Odisha, India,E-mail: brojokishoremishra@gmail.com
xContributorsChandan KonerDr. B. C. Roy Engineering College, Durgapur, West Bengal, IndiaMishra Sambit KumarDepartment of Computer Science and Engineering, Gandhi Institute for Education and Technology,Bhubaneswar, Odisha, India, E-mail: sambitmishra@gietbbsr.comRaghvendra KumarAssociate Professor, Computer Science & Engineering Department, GIET University, IndiaE-mail: raghvendraagrawal7@gmail.comChandrakanta MahantyDepartment of CSE & IT, GIET University, Gunupur, Odisha, IndiaK. MandalAssistant Professor, School of Computing Science and Engineering, Galgotias University,Uttar Pradesh, India, E-mail: kuppanmandal@gmail.comBrojo Kishore MishraDepartment of Computer Science and Engineering, & IT, GIET University, Gunupur, Odisha, India,E-mail: brojokishoremishra@gmail.comAnirban MitraAmity University, Kolkata, West Bengal, IndiaDevpriya PandaDepartment of CSE & IT, GIET University, Gunupur, Odisha, IndiaSubrata PaulRearch Scholar, MAKAUT, and Annex College, Kolkata, West Bengal, India,E-mail: subratapaulcse@gmail.comSushree Bibhuprada B. PriyadarshiniInstitute of Technical Education and Research, Siksha ‘O’ Anusandhan (Deemed to be University),Bhubaneswar, India, E-mail: bimalabibhuprada@gmail.comR. SathiyarajAssistant Professor, School of Computing Science and Engineering, Galgotias University,Uttar Pradesh, India, E-mail: sathiya.peace@gmail.comM. Lawanya ShriSchool of Information Technology and Engineering, VIT, Vellore, IndiaPrasad Suman SouravDepartment of MCA, Ajay Binay Institute of Technology, Cuttack, Odisha, India,E-mail: prasadsuman800@rediffmail.com
ONJCRMDBMTDDMTDeepNMTDMDTECEN - verbartificial intelligenceassociation rule miningbeam size of resulting translationsbuilding management systemsBayesian netcontent analysiscorpus-based machine translationcorpus-driven machine translationcomputational intelligencecross language retrieval systemsconjunctioncustomer relationship managementdictionary based machine translationdata-driven machine translationdeep neural machine translationdata miningdecision treeexpectation confirmationEnglish to Frenchfalse negativesfruit fly algorithmfalse positivesfuzzy unordered rule inductiongenetic algorithmgeneralized additive modelgradient boostinggeneralized linear modelGoogle neural machine translationgeneralized regression neural networkhierarchical agglomerative clusteringhidden Markov model
SBISGSMARTSMOSMTSVMAbbreviationshybrid machine translationinstance-based learninginformation extractioninformation retrievalknowledge discovery from dataK-nearest-neighborskey-performance indicatorslearning algorithmlogistic regressionlatent semantic indexingmodel combinationmultidimensional knapsack problemnounNaive Bayesnamed entity recognitionnatural language generationnatural language processingnatural language toolkitnatural language understandingneural machine translationneural networksnoun-nominativenoun-sociativeoptical character recognitionopen source neural machine translationweb ontology languageparallel multimedia information retrievalprincipal component analysisprepositionrelational databasesresource description frameworkrandom forestsocial business intelligencesemantic graphsspecific, measurable, attainable, realistic, and time-sensitivesequential minimal optimizationstatistical machine translationsupport vector machine
SNWWWxiiisemantic web of thingsterm frequencytext miningtranslation memorytrue negativestrue positivestarget rating pointverbverb finitevariability inflation factorverb nonfinitevector space demonstrateword-sense disambiguationwireless sensor networksWorld Wide Web
PrefaceNatural language processing (NLP) enables communication between peopleand computers and automatic translation to enable people to interact easilywith others around the world. The extraordinary development of the internetand the explosion of textual data on the web have boosted the developmentof the natural language processing field and have especially led to the revivalof corpus based NLP and linguistics. Computational and technologicaldevelopments that incorporate natural language are proliferating. Adequatecoverage encounters difficult problems related to partiality, under specification, and context-dependency, which are signature features of information innature and natural languages. Furthermore, agents (humans or computationalsystems) are information conveyors, interpreters, or participate as components of informational content. Generally, language processing depends onagents’ knowledge, reasoning, perspectives, and interactions.The aim of this edited book is to foster interactions among researchersand practitioners in NLP, AI, and allied areas. The edited book coverstheoretical work, advanced applications, approaches, and techniques forcomputational models of information and its presentation by language(artificial, human, or natural in other ways). The goal is to promote intelligent natural language processing (NLP) and related models of thought,mental states, reasoning, and other cognitive processes.The book is organized into thirteen chapters. Chapter 1 presents a reviewof the entire process of business intelligence, and then brings out insights onhow this platform is used in order to undertake decisions by means of socialnetworks.Chapter 2 deals with the basic concepts of information retrieval (IR)systems, their needs, models of information retrieval systems, and otherrelated concepts, like stemming, indexing, etc. The chapter will help scholarsand young professionals to get critical information required for developingIR systems.Chapter 3 explains all forms of neural machine translation (NMT),with complete translation of a process that involves a neural network,which produces a number of accessible inputs to find the best possibleoutput according to utilization. This kind of translation applies multiple
xviPrefacestrategies on different stages for translation. Stage one implements thetranslated based on words with a complete sentence, and Stage 2 implements the translated on a model over the word within the sentence context.The solidity of neural machine translation allows the learning ability overpoint-to-point bases on the background knowledge input to the predicabletarget output. The chapter also includes a brief discussion on various kindsof neural machine translation conversion principles, such as like Googleneural machine translation (GNMT), open source neural machine translation (OpenNMT), deep neural machine translation (DeepNMT), and so on.Chapter 4 discusses how natural language processing may be linked toa
how natural language processing techniques can be used to prevent phishing attacks, and more. This volume will be a useful and informative resource for faculty, advanced-level students, and professionals in the field of artificial intelligence, natural language processing, and other areas”-- Provided by publisher.
understanding of language. Natural language processing is used to translate text, summarize large files, and provide sentiment analysis, among other applications. Natural Language Processing Overview 7 In Insurance: Natural language processing is often used in conjunction with machine learning models to extract information from unstructured data.
This is a book about Natural Language Processing. By "natural language" we mean a language that is used for everyday communication by humans; languages such as Eng-lish, Hindi, or Portuguese. In contrast to artificial languages such as programming lan-guages and mathematical notations, natural languages have evolved as they pass from
Rudolf Rosa - Deep Neural Networks in Natural Language Processing 14/116 ML in Natual Language Processing Before: complex multistep pipelines Preprocessing, low-level processing, high-level processing, classification, post-processing Massive feature engineering, linguistic knowledge Now: monolitic end-to-end systems (or nearly)
processing. More recently, neural network models started to be applied also to textual natural language signals, again with very promising results. This tutorial surveys neural network models from the perspective of natural language processing research, in an attempt to bring natural-language researchers up to speed with the neural techniques.
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This Artificial Intelligence Master's Program provides training for the most sought after skills required for a successful career in Artificial Intelligence. As you undertake your Artificial Intelligence Engineer training, you will master the concepts of Deep Learning, Machine Learning, Natural Language Processing plus
Natural language processing may be defined as a computer's "way of processing language as actually used rather than set commands." Jones . the details of just how current information retrieval features work and are applied are left vague, which is in part due to the short nature of Spectrum articles, but may also be a result of the .
The classical approach to public administration, derived from Weber, Wilson and Taylor, largely . Classical and Modern Approaches to Public Administration * Polya Katsamunska is a Ph.D., associate professor at the Public Administration and Regional Development of UNWE, e-mail: polya_katsamunska@yahoo.com. 75 Articles is really impressive and yet "almost no national government would argue .
