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ویرایش: [1st ed. 2022] نویسندگان: Deepak Garg (editor), Sarangapani Jagannathan (editor), Ankur Gupta (editor), Lalit Garg (editor), Suneet Gupta (editor) سری: ISBN (شابک) : 303095501X, 9783030955014 ناشر: Springer سال نشر: 2022 تعداد صفحات: 718 [708] زبان: English فرمت فایل : PDF (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود) حجم فایل: 95 Mb
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در صورت تبدیل فایل کتاب Advanced Computing: 11th International Conference, IACC 2021, Msida, Malta, December 18–19, 2021, Revised Selected Papers (Communications in Computer and Information Science, 1528) به فرمت های PDF، EPUB، AZW3، MOBI و یا DJVU می توانید به پشتیبان اطلاع دهید تا فایل مورد نظر را تبدیل نمایند.
توجه داشته باشید کتاب محاسبات پیشرفته: یازدهمین کنفرانس بین المللی، IACC 2021، Msida، مالت، 18-19 دسامبر 2021، مقالات منتخب اصلاح شده (ارتباطات در علوم کامپیوتر و اطلاعات، 1528) نسخه زبان اصلی می باشد و کتاب ترجمه شده به فارسی نمی باشد. وبسایت اینترنشنال لایبرری ارائه دهنده کتاب های زبان اصلی می باشد و هیچ گونه کتاب ترجمه شده یا نوشته شده به فارسی را ارائه نمی دهد.
این جلد شامل مقالات بررسیشده و برگزیده از یازدهمین
کنفرانس بینالمللی محاسبات پیشرفته، IACC 2021، که در دسامبر
2021 برگزار شد، است.
47 مقاله کامل و 4 مقاله کوتاه ارائهشده در این جلد بهطور کامل
بررسی و از بین 246 مورد ارسالی انتخاب شدند. مقالات در بخشهای
موضوعی زیر سازماندهی شدهاند: کاربرد هوش مصنوعی و یادگیری ماشین
در مراقبتهای بهداشتی. استفاده از هوش مصنوعی برای پیش بینی
احساسات و رفتار؛ حل مسئله با استفاده از یادگیری تقویتی و تجزیه
و تحلیل داده ها؛ استفاده های پیشرفته از RNN و تکنیک های
رگرسیون. مداخله ویژه هوش مصنوعی.
This volume constitutes reviewed and selected papers
from the 11th International Advanced Computing Conference,
IACC 2021, held in December 2021.
The 47 full papers and 4 short papers presented in the volume
were thorougly reviewed and selected from 246 submissions. The
papers are organized in the following topical sections:
application of artificial intelligence and machine learning in
healthcare; application of AI for emotion and behaviour
prediction; problem solving using reinforcement learning and
analysis of data; advance uses of RNN and regression
techniques; special intervention of AI.
Preface Organization Contents Editors Application of Artificial Intelligence and Machine Learning in Healthcare Relating Design Thinking Framework in Predicting the Spread of COVID in Tamilnadu Using ARIMA Abstract 1 Introduction 2 Data Depiction 3 Forecasting Models 4 ARIMA Used for Forecasting COVID in Near Future 5 Conclusion References Covid Alert System: A Smart Security System to Alert Violations of Covid Protocol Using OpenCV Abstract 1 Introduction 2 Related Works 3 Proposed Model 4 Methodology 5 Result 6 Conclusion and Future Enhancement References Corona Virus Detection Using EfficientNet from CT Scans Abstract 1 Introduction 1.1 Why CT Screenings? 1.2 Existing Systems 1.3 VGG-16 1.4 ResNet-50 2 Literature Review 3 Deep Learning Models for Covid Detection 3.1 EfficientNet B0 Architecture 3.2 ResNet50 Architecture 4 Experimental Results 5 Conclusion References Disease Diagnosis in Grapevines – A Hybrid Resnet-Jaya Approach 1 Introduction 2 Related Work 3 Datasets Used 4 Proposed Methodology 4.1 Residual Networks (Resnet) 4.2 Minimised Jaya Algorithm – Hybrid NN Approach 5 Experimental Results and Analysis 5.1 Computation Environment 5.2 Optimum Learning Rate Selection 5.3 Cyclical Annealing of the Learning Rate 5.4 Handling Confident Inaccuracies 5.5 Accuracy Analysis and Comparison with Previous Work 5.6 Different CNN Model Comparisons 5.7 Hybrid Jaya Algorithm Approach Compared with Other Optimisation Algorithms 6 Conclusion References Covid-19 Detection Using X-Ray Image Abstract 1 Introduction 2 Literature Review 3 Methodology 3.1 Flow Chart 3.2 Phases of Model: 4 Experimentation 5 Results and Analysis 6 Limitations 7 Conclusion References Alzheimer's Disease Classification Using Transfer Learning 1 Introduction 1.1 Related Work 1.2 Organization 2 Proposed Methodology 2.1 Transfer Learning 2.2 Convolutional Neural Networks 2.3 VGG-19 2.4 Inception-V3 2.5 ResNet-50 2.6 DenseNet-169 3 Performance Evaluation Parameter 3.1 Data Set 3.2 Results and Discussion 4 Conclusion References A Comparative Study of Deep Learning Models for Detecting Pulmonary Embolism 1 Introduction 2 Materials 3 Methodology 3.1 Preprocessing 3.2 Neural Network Module 3.3 Training Parameters 3.4 Models Used for Comparison 3.5 Post Processing 4 Results 5 Conclusion 6 Future Scope References A Novel Compressed and Accelerated Convolution Neural Network for COVID-19 Disease Classification: A Genetic Algorithm Based Approach 1 Introduction 2 Materials and Methods 2.1 Covid Disease Image Dataset 2.2 Architecture of Convolution Neural Network for Disease Classification 3 Results and Discussion 3.1 Performance of ML Classifiers 4 CNN Compression 5 Conclusion References Artificial Intelligence is Not a Foe But a Friend in the Healthcare Sector Abstract 1 Introduction 2 Review of Literature 3 Research Methodology 4 Analysis and Interpretation 4.1 Discussion of the Model 5 Conclusion and Recommendation 6 Limitations and Scope for Future Study References AI and The Cardiologist-When Mind, Heart and Machine Unite Abstract 1 Introduction 2 A Brief Introduction to AI Principles for the Clinician 2.1 Machine Learning and Deep Learning 2.2 Natural Language Processing 3 Artificial Intelligence in Cardiology 3.1 Electrophysiology 3.2 Echocardiography 3.2.1 Stress Echocardiography 3.3 Clinical Decision Support and Preventive Cardiology 3.4 Wearable Sensors 4 Moving Forward: Future Prospects References An Analysis of the Psychological Implications of COVID-19 Pandemic on Undergraduate Students and Efforts on Mitigation 1 Introduction 2 Literature Review 2.1 SARS and Ebola Epidemics 2.2 Psychological Effect of COVID-19 on General Population 2.3 Psychological Effect of COVID-19 on Student Population 2.4 Technology 3 Methods 3.1 Study Design and Participants 4 Results and Discussion 4.1 Dhriti - Multilingual Chatbot for Mental Health Support 4.2 Discussion 4.3 Best Practices and Limitations of the Study 5 Conclusion and Future Work References Network-Based Identification of Module Biomarker Associated with Hepatocellular Carcinoma Abstract 1 Introduction 1.1 Epidemiology 1.2 Risk Factors 1.3 Pathophysiology of HCC 1.4 MicroRNA (miRNA) Biomarkers 1.5 Systems Biology for Identification 2 Materials and Methods 2.1 TCGA miRNA-Seq Data Extraction and Differential Expression Analysis 2.2 miRNA Co-expression Network Construction and Module Detection 2.3 Overall Survival (OS) Analysis 3 Results and Discussion 3.1 TCGA miRNA-Seq Data Extraction and Differential Expression Analysis 3.2 miRNA Co-expression Network Construction and Module Detection 3.3 OS Analysis 4 Conclusion References Identifying Hub Nodes and Sub-networks from Cattle Rumen Microbiome Multilayer Networks Abstract 1 Introduction 2 Method 3 Results 3.1 Multilayer Network 3.2 Node Hub Ranked Based on Topological Properties 3.3 Biological Function Analysis 4 Discussion 5 Conclusion References Application of AI for Emotion and Behaviour Prediction Machine Learning-Based Psychology: A Study to Understand Cognitive Decision-Making Abstract 1 Introduction 2 Related Work 3 Methodology 3.1 Sample and Data Collection 3.2 Data Analytics 3.3 Technology Stack 4 Results 4.1 Case Studies 4.2 Findings 4.3 Visualiations 5 Implication and Limitation 6 Conclusion and Future Scope References Predicting Stock Market Prices Using Sentiment Analysis of News Articles Abstract 1 Introduction 2 Related Work 3 Proposed Method 4 Description of Data Set and Its Pre-processing 4.1 Data Collection 4.2 Data Processing 4.3 Stock Prediction 5 Results 6 Conclusion References Sentimental Analysis on Multi-domain Sentiment Dataset Using SVM and Naive Bayes Algorithm Abstract 1 Introduction 2 Related Works 3 Proposed Methodolgy 3.1 Naive Bayes Approach 3.2 SVM 4 Results and Discussion 4.1 Accuracy Classification 4.2 Confusion Matrix 5 Conclusion References Artificial Intelligence in Online Stores' Processes 1 Introduction 2 AI in Online Marketing 2.1 Facebook Advertising 2.2 Amazon Advertising 2.3 Google - Smart Ads 3 AI in an e-Commerce Fulfillment Center 4 AI in Barcode Identification 5 New AI-Driven Delivery Methods in E-Commerce 5.1 Autonomous Delivery Robots 5.2 Deliveries by Aerial Drones 5.3 Deliveries Using 3D Printing 6 Conclusions and Discussion References Early Warning Indicators for Financial Crisis During Covid-19 1 Introduction 2 Methodology 2.1 Detrending 2.2 Early Warning Signal (EWS) Indicators 3 Results and Discussion 4 Conclusion References Facial Recognition Based Attendance Monitoring System 1 Introduction 2 Literature Study 3 Methodology 3.1 Framework 4 Design Approach 4.1 Module 1 4.2 Module 2 4.3 Module 3 4.4 Module 4 4.5 Module 5 4.6 Module 6 5 Results and Analysis 6 Conclusion and Future Work References Transfer Learning Using Variational Quantum Circuit 1 Introduction 2 Background 3 Related Works 4 The Hybrid Model 4.1 Transfer Learning 4.2 Proposed Model 4.3 Dressed Quantum Circuit 5 Testing 6 Results 7 Discussion 8 Future Work References Problem Solving Using Reinforcement Learning and Analysis of Data Gait Learning Using Reinforcement Learning 1 Introduction 2 Related Work 3 Design and Learning Process 4 Interfacing with the Real World Quadruped 5 Results of Simulation 6 Discussion 7 Conclusion and Future Work References Data Science in the Business Environment: Architecture, Process and Tools Abstract 1 Introduction 2 Architecture and Framework 2.1 Data Science Conceptual Architecture 2.2 EDISON Data Science Framework 2.3 Case Study: Data Science Degree Apprenticeship 3 Methodology and Process 3.1 Range of Approaches 3.2 A Process Model for Data-Driven Decision Making 3.3 Case Study: Customer Analytics in SMEs 4 Tools and Techniques 4.1 EDISON Data Science Skills 4.2 Analytical Technology 4.3 Case Study: Marketing Analytics for Health Insurance 4.3.1 Explore Data 4.3.2 Discover Insights 5 Conclusion References A Logarithmic Distance-Based Multi-Objective Genetic Programming Approach for Classification of Imbalanced Data 1 Introduction 2 Materials and Methods 2.1 Multi-Objective Genetic Programming (MOGP) 2.2 Proposed MOGP Approach 2.3 Trapezoidal Rule for Area Under Generated Pareto-Front 2.4 GP Parameter Setting 2.5 Benchmark Data Set 3 Results and Discussion 4 Conclusions References Multiview Classification with Missing-Views Through Adversarial Representation and Inductive Transfer Learning 1 Introduction 1.1 Motivation and Contributions 2 Related Work 3 Proposed Methodology 3.1 Adversarial Cross-View Latent Learning 3.2 Classification Through an Inductive Transfer of Encodings 4 Experimental Setup 4.1 Datasets 4.2 Evaluation Metrics 5 Results Analysis and Discussion 5.1 Performance on Existing Multiview State-of-the-Art Systems 5.2 Performance Evaluation on Handling the Missing-Views in Multiview Data 6 Conclusion and Future Perspectives References Deep Reinforcement Learning Based Throughput Maximization Scheme for D2D Users Underlaying NOMA-Enabled Cellular Network 1 Introduction 1.1 Related Work 1.2 Motivation and Contributions 1.3 Organization 2 System Model and Problem Formulation 2.1 Channel Model 2.2 Throughput Calculation 2.3 Problem Formulation 3 Proposed Solution 3.1 Centralised Optimisation 3.2 Proximal Policy Optimization 4 Performance Evaluation 4.1 Numerical Settings 4.2 Results and Discussion 5 Conclusion References An Intrusion Detection System for Blackhole Attack Detection and Isolation in RPL Based IoT Using ANN 1 Introduction 2 Black Hole Attack in RPL Scenario 3 Related Work 4 INSULATE - The Proposed Intrusion Detection System 4.1 System Model 4.2 Local Detection 4.3 Global Detection and Eviction 5 Performance Evaluation 5.1 Simulation Setup and Performance Metrics 5.2 Simulation Results and Performance Comparison 6 Conclusion References Evaluating the Efficacy of Different Neural Network Deep Reinforcement Algorithms in Complex Search-and-Retrieve Virtual Simulations Abstract 1 Introduction 2 Background 2.1 Proximal-Policy Optimization (PPO) 2.2 Soft-Actor Critic (SAC) 3 Methods 3.1 Experimental Design 4 Performance Metric 5 Results 5.1 Training Results 5.2 Test Results 5.3 Influence of Number of Hidden Layers of the Neural Network on Model Performance 5.4 Influence of Number of Nodes of the Neural Network on Model Performance 6 Discussion 7 Future Scope 8 Conclusion Acknowledgements References Post-hoc Explainable Reinforcement Learning Using Probabilistic Graphical Models 1 Introduction 2 Related Work 3 Methods 3.1 Reinforcement Learning (RL) 3.2 Explainable Reinforcement Learning (XRL) 3.3 Probabilistic Graphical Model (PGM) 4 Explainability and Reinforcement Learning 5 Experimental Setup 6 Results and Discussions 6.1 Environment I : Taxi-V2 6.2 Environment II: FrozenLake-V0 6.3 Discussion 7 Limitations and Future Work 8 Conclusion References Ghostbusters: How the Absence of Class Pairs in Multi-Class Multi-Label Datasets Impacts Classifier Accuracy 1 Introduction 2 Related Work 3 Experimental Setup 4 Experiments 4.1 Experiment 1: Impact of Ratio Bias 4.2 Experiment 2: Impact of Parity Bias 4.3 Experiment 3: Impact of Degree of Separation 4.4 Experiment 4: Adding Connected Examples to the MCML Classifier 5 Discussion 6 Future Work 7 Conclusion 8 Appendix References ReLearner: A Reinforcement Learning-Based Self Driving Car Model Using Gym Environment 1 Introduction 2 Related Works 3 ReLearner Model 3.1 No Reinforcement Learning 3.2 Q-learning 4 Experimental Results 5 Conclusion References Automating Paid Parking System Using IoT Technology Abstract 1 Introduction 2 Literature Review 3 Architectural Diagram 4 Proposed Model 4.1 Classification of Vehicles 4.2 Real Time Number Plate Detection 4.3 Character Segmentation and Recognition 4.4 IOT Using RPi 4.5 PayPark Application 5 Observations and Results 6 Conclusion 7 Future Scope References Farmers' Survey App - An Interactive Open-Source Application for Agricultural Survey 1 Introduction 2 Key Features of the Android Application 3 Application Interface and Architecture of Survey App 3.1 Application Interface 3.2 The Architecture of the Survey App 4 Case Study: Analysis of Survey Data 5 Conclusion References Advance Uses of RNN and Regression Techniques Improving Recognition of Handwritten Kannada Characters Using Mixup Regularization Abstract 1 Introduction 2 Literature Survey 3 Dataset 3.1 Kannada84 3.2 Char74K 4 Proposed Methodology 4.1 Pre-processing 4.2 Augmentation 5 Architecture 5.1 VGG Network 5.2 Residual Neural Network 5.3 Squeeze-and-Excitation Networks 5.4 Improving Performance with Mixup 6 Training 7 Results 8 Conclusion and Future Work References Research on the Detection and Recognition Algorithm of Click Chinese Character Verification Code Abstract 1 Introduction 2 Solution Idea 3 Detection Experiment 3.1 K-means Clustering Generates Anchor Size 3.2 Class Imbalance 4 Recognition Experiment 4.1 Main Idea 4.2 Feature Extraction Network 4.3 Difference of Gaussian 4.4 Similarity Calculation 5 Conclusion References Multihead Self-attention and LSTM for Spacecraft Telemetry Anomaly Detection 1 Introduction 2 LSTM Model for Anomaly Detection 3 MHSA Model for Anomaly Detection 3.1 Positional Encoding 3.2 Architecture 4 Non-parametric Dynamic Thresholding (NPDT) Method 5 Results and Analysis 5.1 Detection of Solar Array Drive Assembly (SADA) Anomaly 5.2 Detection of Momentum Wheel Anomaly 5.3 Detection of Reaction Wheel Anomaly 6 Comparison of the Models 6.1 Number of Parameters 6.2 Empirical Time Complexity of the Models 6.3 Comparing Normalized Anomaly Scores 7 Discussions and Conclusions References Validity and Reliability Assessment of a Smartphone Application for Measuring Chronic Low Back Pain Abstract 1 Introduction 2 Related Work 2.1 Chronic Pain: More Than Just a Physical Problem 2.2 Chronic Low Back Pain (CLBP): Definition and Epidemiology 2.3 Mode of Assessment 3 Problem Formulation 4 Methodology 4.1 Unit Study Design 4.2 Tools 4.3 Testing Procedure 5 Results and Discussions 5.1 Participants 5.2 Readings 5.3 Analysis of Data 5.4 Discussions 5.5 Limitations 6 Conclusions and Future Scope References Predicting Disasters from Tweets Using GloVe Embeddings and BERT Layer Classification Abstract 1 Introduction 2 Literature Survey 2.1 Text Classification Using Machine Learning Techniques 2.2 Sentimental Analysis of Twitter Data Using Classifier Algorithms 2.3 Event Classification and Retrieving User’s Geographical Location Based on Live Tweets on Twitter and Prioritizing Them to Alert the Concern Authority 2.4 Automatic Classification of Disaster-Related Tweets 2.5 Comparing BERT Against Traditional Machine Learning Text Classification 2.6 Usage and Analysis of Twitter During 2015 Chennai Flood Towards Disaster Management 2.7 A Comparative Analysis of Machine Learning Techniques for Disaster-Related Tweet Classification 2.8 Multimodal Analysis of Disaster Tweets 3 Methodology 3.1 Data Exploration 3.2 Meta Features Extraction 3.3 Text Cleaning and Preprocessing 3.4 Cardinality and Target Distribution 3.5 Target Features 3.6 Architecture of the Disaster Detector Function 3.7 Word Embedding Using GloVe 3.8 Classification Using BERT Model 4 Results 5 Conclusion References Contextual Quality Assessment of the Newspaper Articles Based on Keyword Extraction 1 Introduction 2 Related Works and Our Contributions 3 Preliminaries 3.1 Quality of Document 3.2 Graph Centrlity Metrics 3.3 Clustering Coefficient 3.4 Mantel Test 4 Our Approach for Quality Detection of Any Article 4.1 Representation of the Text Report with Graph 4.2 Analysing the Generated Graph 4.3 Features 4.4 Illustration with an Example 5 Result and Analysis 5.1 Comparison with Other Existing Methods 5.2 Result on Real-Life Application 5.3 Result on Newspaper Data 5.4 Limitations 6 Conclusions References GEDset: Automatic Dataset Builder for Machine Translation System with Specific Reference to Gujarati-English Abstract 1 Introduction 2 Motivation and Significance 3 Software Description 3.1 Software Architecture 3.2 Software Functionalities 4 Proposed Algorithm 5 Experiment and Result 6 Conclusion References Power Function Algorithm for Linear Regression Weights with Weibull Data Analysis Abstract 1 Introduction 2 Asymptotic Power Functions 3 Weibull Parameter Estimation by WLR 3.1 Weighted Linear Regression 3.2 Variances of the Plotting Position Z 4 Power Model for LR Weights 4.1 Infinite Sample Size 4.2 Finite Sample Size 5 Evaluation of the Algorithm 6 Discussion and Conclusion References Special Intervention of AI Shrub Detection in High-Resolution Imagery: A Comparative Study of Two Deep Learning Approaches 1 Introduction 2 Approach 2.1 Dataset and Target Plant 2.2 CNN-Based Detection Approach 2.3 Segmentation Approach 2.4 Evaluation 3 Experimental Evaluation 3.1 Classification of Ideal Image Patches 3.2 Detection – Classification of Proposed Windows 3.3 Deep Learning-Based Semantic Segmentation 3.4 Comparative Results 4 Discussion 5 Conclusion References Optimized Deep Neural Network for Tomato Leaf Diseases Identification Abstract 1 Introduction 2 Optimized Deep Neural Network for Tomato Leaf Diseases (ODNN-TLD) 2.1 Data Preparation 2.2 Data Pre-processing 2.3 Training the Proposed Model with VGG16 and CNN (ODNN-TLD) 2.4 Optimizing Functions 3 Results and Discussion 4 Conclusion Acknowledgement References Application of Distributed Back Propagation Neural Network for Dynamic Real-Time Bidding 1 Introduction 2 Background 2.1 Real-Time Bidding 2.2 Distributed Back Propagation Neural Networks (d-bpnn) 3 Working of Bidding Strategies 3.1 Flat Bidding 3.2 Randomized Bidding 3.3 ML Bidding 4 Empirical Evaluation and Discussion 4.1 Parameters of Evaluation 4.2 Description of Dataset 4.3 Experimental Setup and Results 5 Conclusions References An Efficient Minimum Spanning Tree-Based Color Image Segmentation Approach Abstract 1 Introduction 2 Related Works 3 Proposed Methodology 4 Experimental Setup 4.1 Dataset Used 4.2 Evaluation Parameters 5 Experimental Results and Discussion 6 Conclusion and Future Perspective References Geo-ML Enabled Above Ground Biomass and Carbon Estimation for Urban Forests Abstract 1 Introduction 2 Materials and Methods 2.1 Study Area 2.2 Satellite Data 2.3 Field Sampling 2.4 Field Observed AGB and Carbon Estimation for Urban Forest 3 Methods 3.1 Geospatial Modelling of AGB and Carbon 3.2 Variable Selection 3.3 RF Based Approach 4 Results and Discussion 4.1 Ground Observed AGB and Carbon Estimation 4.2 AGB Estimation Using RF 4.3 Spatial Distribution of AGB and Carbon 5 Conclusion References Custom Cloud: An Efficient Model for Cloud Service Selection Based on Neural Network Abstract 1 Introduction 1.1 Motivation and Contributions 1.2 Paper Outline 2 Proposed Custom Cloud Model 3 Case Study 4 Experimental Results and Discussion 5 Conclusion Data and Code Availability References A Machine Learning-Based Approach for Efficient Cloud Service Selection Abstract 1 Introduction 1.1 Paper Outline 2 Literature Survey 3 Problem Statement 4 Experimental Results and Discussion 5 Conclusion References Enhancing Network Robustness Using Statistical Approach Based Rewiring Strategy 1 Introduction 2 Literature Review 3 Definitions 4 Proposed Strategies 4.1 Betweenness Centrality and Core Periphery (BCCP) Based Rewiring Strategy 4.2 Clustering Coefficient and Betweenness Centrality (CCBC) Based Rewiring Strategy 5 Results 6 Conclusions References A Partcle Swarm Optimization Based Approach for Filter Pruning in Convolution Neural Network for Tomato Leaf Disease Classification 1 Introduction 2 Materials and Methods 2.1 Dataset 2.2 Proposed Model 3 Experimental Results 3.1 Pre-trained CNN Models Performance 3.2 Performance of Machine Learning Methods 4 CNN Model Compression 5 Conclusion References Data Breach in Social Networks Using Machine Learning Abstract 1 Introduction 2 Literature Review 3 Theoretical Background 3.1 Breach Methods 3.2 What Causes Data Breaches? 3.3 Recent Data Breaches & Statistics 3.4 Data Analysis 4 Results 5 Conclusion References Sentiment Analysis of Customers Review Using Hybrid Approach Abstract 1 Introduction 1.1 Natural Language Processing 1.2 Sentiment Analysis 1.3 Objective of Sentiment Analysis 1.4 Sentiment Analysis Approach for Prediction 1.5 Different Types of Sentiment Analysis 2 Literature Review 3 Problem Statement 4 Proposed Model 4.1 Objective of Proposed Work 4.2 Working of Proposed Work 5 Result and Discussion 5.1 Accuracy Comparison 5.2 Performance Comparison 6 Conclusion 7 Scope of Research References Author Index