Natural Language Processing for Software Engineering

Rajesh Kumar Chakrawarti, PhD, is a dean and professor in the Department of Computer Science and Engineering at Sushila Devi Bansal College, Bansal Group of Institutions, India. He has over 20 years of professional experience in academia and industry. Additionally, he has organized and attended over 200 seminars, workshops, and conferences and has published over 100 research papers and book chapters in nationally and internationally revered publications. Ranjana Sikarwar is currently pursuing a PhD from Amity University, Gwalior. She completed her Bachelor of Engineering in 2006 and Master of Technology in Computer Science and Engineering in 2015. Her research interests include social network analysis, graph mining, machine learning, Internet of Things, and deep learning. Sanjaya Kumar Sarangi, PhD, is an adjunct professor and coordinator at Utkal University with over 23 years of experience in the academic, research, and industry sectors. He has a number of publications in journals and conferences, has authored many textbooks and book chapters, and has more than 30 national and international patents. He is an active member and life member of many associations, as well as an editor, technical program committee member, and reviewer in reputed journals and conferences. He has dedicated his career to advancing information and communication technology to enhance and optimize worldwide research and information dissemination, leading to improved student learning and teaching methods. Samson Arun Raj Albert Raj, PhD, is an assistant professor and placement coordinator in the Division of Computer Science and Engineering, School of Computer Science and Technology, Karunya Institute of Technology and Sciences, Tamil Nadu, India. His research is focused on smart city development using drone networks and energy grids with various applications, and his areas of expertise include wireless sensor networks, vehicular ad-hoc networks, and intelligent transportation systems. Shweta Gupta is an assistant professor in the Computer Science and Engineering Department at Medicaps University, Indore (M.P.), India. She focuses on natural language processing, data mining, and machine learning. She aims to close the knowledge gap between theory and real-world applications in the tech sector through her passion for research and teaching. Her approach centers on encouraging creativity and motivating students to strive for technological excellence. Krishnan Sakthidasan Sankaran, PhD, is a professor in the Department of Electronics and Communication Engineering at Hindustan Institute of Technology and Science, India. He has been a senior member of the Institute of Electrical and Electronics Engineers for the past ten years and has published more than 70 papers in refereed journals and international conferences. He has also published three books to his credit. His research interests include image processing, wireless networks, cloud computing, and antenna design. Romil Rawat has attended several research programs and received research grants from the United States, Germany, Italy, and the United Kingdom. He has chaired international conferences and hosted several research events, in addition to publishing several research patents. His research interests include cybersecurity, Internet of Things, dark web crime analysis and investigation techniques, and working towards tracing illicit anonymous contents of cyber terrorism and criminal activities.

• Preface xvii1 Machine Learning and Artificial Intelligence for Detecting Cyber Security Threats in IoT Environmment 1Ravindra Bhardwaj, Sreenivasulu Gogula, Bidisha Bhabani, K. Kanagalakshmi, Aparajita Mukherjee and D. Vetrithangam1.1 Introduction 21.2 Need of Vulnerability Identification 41.3 Vulnerabilities in IoT Web Applications 51.4 Intrusion Detection System 71.5 Machine Learning in Intrusion Detection System 101.6 Conclusion 12References 122 Frequent Pattern Mining Using Artificial Intelligence and Machine Learning 15R. Deepika, Sreenivasulu Gogula, K. Kanagalakshmi, Anshu Mehta, S. J. Vivekanandan and D. Vetrithangam2.1 Introduction 162.2 Data Mining Functions 172.3 Related Work 192.4 Machine Learning for Frequent Pattern Mining 242.5 Conclusion 26References 263 Classification and Detection of Prostate Cancer Using Machine Learning Techniques 29D. Vetrithangam, Pramod Kumar, Shaik Munawar, Rituparna Biswas, Deependra Pandey and Amar Choudhary3.1 Introduction 303.2 Literature Survey 323.3 Machine Learning for Prostate Cancer Classification and Detection 353.4 Conclusion 37References 384 NLP-Based Spellchecker and Grammar Checker for Indic Languages 43Brijesh Kumar Y. Panchal and Apurva Shah4.1 Introduction 444.2 NLP-Based Techniques of Spellcheckers and Grammar Checkers 444.2.1 Syntax-Based 444.2.2 Statistics-Based 454.2.3 Rule-Based 454.2.4 Deep Learning-Based 454.2.5 Machine Learning-Based 464.2.6 Reinforcement Learning-Based 464.3 Grammar Checker Related Work 474.4 Spellchecker Related Work 584.5 Conclusion 66References 675 Identification of Gujarati Ghazal Chanda with Cross-Platform Application 71Brijeshkumar Y. PanchalAbbreviations 725.1 Introduction 725.1.1 The Gujarati Language 725.2 Ghazal 755.3 History and Grammar of Ghazal 775.4 Literature Review 785.5 Proposed System 855.6 Conclusion 92References 926 Cancer Classification and Detection Using Machine Learning Techniques 95Syed Jahangir Badashah, Afaque Alam, Malik Jawarneh, Tejashree Tejpal Moharekar, Venkatesan Hariram, Galiveeti Poornima and Ashish Jain6.1 Introduction 966.2 Machine Learning Techniques 976.3 Review of Machine Learning for Cancer Detection 1016.4 Methods 1036.5 Result Analysis 1066.6 Conclusion 107References 1087 Text Mining Techniques and Natural Language Processing 113Tzu-Chia Chen7.1 Introduction 1137.2 Text Classification and Text Clustering 1157.3 Related Work 1167.4 Methodology 1217.5 Conclusion 123References 1238 An Investigation of Techniques to Encounter Security Issues Related to Mobile Applications 127Devabalan Pounraj, Pankaj Goel, Meenakshi, Domenic T. Sanchez, Parashuram Shankar Vadar, Rafael D. Sanchez and Malik Jawarneh8.1 Introduction 1288.2 Literature Review 1308.3 Results and Discussions 1378.4 Conclusion 138References 1399 Machine Learning for Sentiment Analysis Using Social Media Scrapped Data 143Galiveeti Poornima, Meenakshi, Malik Jawarneh, A. Shobana, K.P. Yuvaraj, Urmila R. Pol and Tejashree Tejpal Moharekar9.1 Introduction 1449.2 Twitter Sentiment Analysis 1469.3 Sentiment Analysis Using Machine Learning Techniques 1499.4 Conclusion 152References 15210 Opinion Mining Using Classification Techniques on Electronic Media Data 155Meenakshi10.1 Introduction 15610.2 Opinion Mining 15810.3 Related Work 15910.4 Opinion Mining Techniques 16110.4.1 Naïve Bayes 16210.4.2 Support Vector Machine 16210.4.3 Decision Tree 16310.4.4 Multiple Linear Regression 16310.4.5 Multilayer Perceptron 16410.4.6 Convolutional Neural Network 16410.4.7 Long Short-Term Memory 16510.5 Conclusion 166References 16611 Spam Content Filtering in Online Social Networks 169Meenakshi11.1 Introduction 16911.1.1 E-Mail Spam 17011.2 E-Mail Spam Identification Methods 17111.2.1 Content-Based Spam Identification Method 17111.2.2 Identity-Based Spam Identification Method 17211.3 Online Social Network Spam 17211.4 Related Work 17311.5 Challenges in the Spam Message Identification 17711.6 Spam Classification with SVM Filter 17811.7 Conclusion 179References 18012 An Investigation of Various Techniques to Improve Cyber Security 183Shoaib Mohammad, Ramendra Pratap Singh, Rajiv Kumar, Kshitij Kumar Rai, Arti Sharma and Saloni Rathore12.1 Introduction 18412.2 Various Attacks 18512.3 Methods 18912.4 Conclusion 190References 19113 Brain Tumor Classification and Detection Using Machine Learning by Analyzing MRI Images 193Chandrima Sinha Roy, K. Parvathavarthini, M. Gomathi, Mrunal Pravinkumar Fatangare, D. Kishore and Anilkumar Suthar13.1 Introduction 19413.2 Literature Survey 19713.3 Methods 20013.4 Result Analysis 20213.5 Conclusion 203References 20314 Optimized Machine Learning Techniques for Software Fault Prediction 207Chetan Shelke, Ashwini Mandale (Jadhav), Shaik Anjimoon, Asha V., Ginni Nijhawan and Joshuva Arockia Dhanraj14.1 Introduction 20814.2 Literature Survey 21114.3 Methods 21414.4 Result Analysis 21614.5 Conclusion 216References 21715 Pancreatic Cancer Detection Using Machine Learning and Image Processing 221Shashidhar Sonnad, Rejwan Bin Sulaiman, Amer Kareem, S. Shalini, D. Kishore and Jayasankar Narayanan15.1 Introduction 22215.2 Literature Survey 22515.3 Methodology 22715.4 Result Analysis 22815.5 Conclusion 228References 22916 An Investigation of Various Text Mining Techniques 233Rajashree Gadhave, Anita Chaudhari, B. Ramesh, Vijilius Helena Raj, H. Pal Thethi and A. Ravitheja16.1 Introduction 23416.2 Related Work 23616.3 Classification Techniques for Text Mining 24016.3.1 Machine Learning Based Text Classification 24016.3.2 Ontology-Based Text Classification 24116.3.3 Hybrid Approaches 24116.4 Conclusion 241References 24117 Automated Query Processing Using Natural Language Processing 245Divyanshu Sinha, G. Ravivarman, B. Rajalakshmi, V. Alekhya, Rajeev Sobti and R. Udhayakumar17.1 Introduction 24617.1.1 Natural Language Processing 24617.2 The Challenges of NLP 24817.3 Related Work 24917.4 Natural Language Interfaces Systems 25317.5 Conclusion 255References 25618 Data Mining Techniques for Web Usage Mining 259Navdeep Kumar Chopra, Chinnem Rama Mohan, Snehal Dipak Chaudhary, Manisha Kasar, Trupti Suryawanshi and Shikha Dubey18.1 Introduction 26018.1.1 Web Usage Mining 26018.2 Web Mining 26318.2.1 Web Content Mining 26418.2.2 Web Structure Mining 26418.2.3 Web Usage Mining 26518.2.3.1 Preprocessing 26518.2.3.2 Pattern Discovery 26518.2.3.3 Pattern Analysis 26618.3 Web Usage Data Mining Techniques 26618.4 Conclusion 268References 26919 Natural Language Processing Using Soft Computing 271M. Rajkumar, Viswanathasarma Ch, Anandhi R. J., D. Anandhasilambarasan, Om Prakash Yadav and Joshuva Arockia Dhanraj19.1 Introduction 27219.2 Related Work 27319.3 NLP Soft Computing Approaches 27619.4 Conclusion 279References 27920 Sentiment Analysis Using Natural Language Processing 283Brijesh Goswami, Nidhi Bhavsar, Soleman Awad Alzobidy, B. Lavanya, R. Udhayakumar and Rajapandian K.20.1 Introduction 28420.2 Sentiment Analysis Levels 28520.2.1 Document Level 28520.2.2 Sentence Level 28520.2.3 Aspect Level 28620.3 Challenges in Sentiment Analysis 28620.4 Related Work 28820.5 Machine Learning Techniques for Sentiment Analysis 29020.6 Conclusion 292References 29221 Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data 295C. V. Guru Rao, Nagendra Prasad Krishnam, Akula Rajitha, Anandhi R. J., Atul Singla and Joshuva Arockia Dhanraj21.1 Introduction 29621.2 Web Mining 29821.3 Taxonomy of Web Data Mining 29921.3.1 Web Usage Mining 30021.3.2 Web Structure Mining 30121.3.3 Web Content Mining 30121.4 Web Content Mining Methods 30221.4.1 Unstructured Text Data Mining 30221.4.2 Structured Data Mining 30321.4.3 Semi-Structured Data Mining 30321.5 Efficient Algorithms for Web Data Extraction 30421.6 Machine Learning Based Web Content Extraction Methods 30521.7 Conclusion 307References 30722 Intelligent Pattern Discovery Using Web Data Mining 311Vidyapati Jha, Chinnem Rama Mohan, T. Sampath Kumar, Anandhi R.J., Bhimasen Moharana and P. Pavankumar22.1 Introduction 31222.2 Pattern Discovery from Web Server Logs 31322.2.1 Subsequently Accessed Interesting Page Categories 31422.2.2 Subsequent Probable Page of Visit 31422.2.3 Strongly and Weakly Linked Web Pages 31422.2.4 User Groups 31522.2.5 Fraudulent and Genuine Sessions 31522.2.6 Web Traffic Behavior 31522.2.7 Purchase Preference of Customers 31522.3 Data Mining Techniques for Web Server Log Analysis 31622.4 Graph Theory Techniques for Analysis of Web Server Logs 31822.5 Conclusion 319References 32023 A Review of Security Features in Prominent Cloud Service Providers 323Abhishek Mishra, Abhishek Sharma, Rajat Bhardwaj, Romil Rawat, T.M.Thiyagu and Hitesh Rawat23.1 Introduction 32423.2 Cloud Computing Overview 32423.3 Cloud Computing Model 32623.4 Challenges with Cloud Security and Potential Solutions 32723.5 Comparative Analysis 33223.6 Conclusion 332References 33224 Prioritization of Security Vulnerabilities under Cloud Infrastructure Using AHP 335Abhishek Sharma and Umesh Kumar Singh24.1 Introduction 33624.2 Related Work 33824.3 Proposed Method 34124.4 Result and Discussion 34624.5 Conclusion 352References 35225 Cloud Computing Security Through Detection & Mitigation of Zero-Day Attack Using Machine Learning Techniques 357Abhishek Sharma and Umesh Kumar Singh25.1 Introduction 35825.2 Related Work 36025.2.1 Analysis of Zero-Day Exploits and Traditional Methods 36425.3 Proposed Methodology 36725.4 Results and Discussion 37625.4.1 Prevention & Mitigation of Zero Day Attacks (ZDAs) 38125.5 Conclusion and Future Work 383References 38426 Predicting Rumors Spread Using Textual and Social Context in Propagation Graph with Graph Neural Network 389Siddharath Kumar Arjaria, Hardik Sachan, Satyam Dubey, Ayush Pandey, Mansi Gautam, Nikita Gupta and Abhishek Singh Rathore26.1 Introduction 39026.2 Literature Review 39126.3 Proposed Methodology 39326.3.1 Tweep Tendency Encoding 39426.3.2 Network Dynamics Extraction 39526.3.3 Extracted Information Integration 39626.4 Results and Discussion 39826.5 Conclusion 399References 40027 Implications, Opportunities, and Challenges of Blockchain in Natural Language Processing 403Neha Agrawal, Balwinder Kaur Dhaliwal, Shilpa Sharma, Neha Yadav and Ranjana Sikarwar27.1 Introduction 40427.2 Related Work 40627.3 Overview on Blockchain Technology and NLP 40927.3.1 Blockchain Technology, Features, and Applications 40927.3.2 Natural Language Processing 41027.3.3 Challenges in NLP 41127.3.4 Data Integration and Accuracy in NLP 41127.4 Integration of Blockchain into NLP 41227.5 Applications of Blockchain in NLP 41427.6 Blockchain Solutions for NLP 41727.7 Implications of Blockchain Development Solutions in NLP 41827.8 Sectors That can be Benified from Blockchain and NLP Integration 41927.9 Challenges 42027.10 Conclusion 422References 42228 Emotion Detection Using Natural Language Processing by Text Classification 425Jyoti Jayal, Vijay Kumar, Paramita Sarkar and Sudipta Kumar Dutta28.1 Introduction 42628.2 Natural Language Processing 42728.3 Emotion Recognition 42928.4 Related Work 43028.4.1 Emotion Detection Using Machine Learning 43028.4.2 Emotion Detection Using Deep Learning 43228.4.3 Emotion Detection Using Ensemble Learning 43528.5 Machine Learning Techniques for Emotion Detection 43728.6 Conclusion 439References 43929 Alzheimer Disease Detection Using Machine Learning Techniques 443M. Prabavathy, Paramita Sarkar, Abhrendu Bhattacharya and Anil Kumar Behera29.1 Introduction 44429.2 Machine Learning Techniques to Detect Alzheimer’s Disease 44529.3 Pre-Processing Techniques for Alzheimer’s Disease Detection 44629.4 Feature Extraction Techniques for Alzheimer’s Disease Detection 44829.5 Feature Selection Techniques for Diagnosis of Alzheimer’s Disease 44929.6 Machine Learning Models Used for Alzheimer’s Disease Detection 45129.7 Conclusion 453References 45430 Netnographic Literature Review and Research Methodology for Maritime Business and Potential Cyber Threats 457Hitesh Rawat, Anjali Rawat and Romil Rawat30.1 Introduction 45830.2 Criminal Flows Framework 46030.3 Oceanic Crime Exchange and Categorization 46230.4 Fisheries Crimes and Mobility Crimes 46930.5 Conclusion 47030.6 Discussion 470References 47031 Review of Research Methodology and IT for Business and Threat Management 475Hitesh Rawat, Anjali Rawat, Sunday Adeola Ajagbe and Yagyanath RimalAbbreviation Used 47631.1 Introduction 47731.2 Conclusion 484References 485About the Editors 487Index 489