AGC 2023: First Analytics Global Conference, AGC 2023, Kolkata, India, April 28–29, 2023, Proceedings (Communications in Computer and Information Science, 2008)

This book constitutes the refereed proceedings of the 1st Analytics Global Conference, AGC 2023, held in Kolkata, India, in April 2023. The AGC conference sought to facilitate industry-academia interfacing in the domain of machine learning and artificial intelligence. The 11 full papers presented in these proceedings were carefully reviewed and selected from 36 submissions. The papers are organized in the two topical sections: Applications of Analytics in Business and Machine Learning & Deep Learning and Text Analytics. Preface Organization Contents Applications of Analytics in Business Efficiency and Benchmarking Using DEA and Tessellation in Retail Stores 1 Introduction 2 Problem Statement 2.1 Background 2.2 Data Overview 3 Methods and Tools 3.1 Voronoi Tesselation 3.2 Data Envelopment Analysis (DEA) 3.3 Technology Stack 4 Implementation 4.1 Voronoi Tesselation 4.2 Data Envelopment Analysis (DEA) 4.3 Other Analyses 5 Outcomes 5.1 Findings: Tessellation and SAM 5.2 Findings: Single Input and 2 Outputs 5.3 Findings: All Inputs and Outputs 5.4 Findings: Charts 6 Discussion 7 Conclusion References A Machine Learning Framework Developed by Leveraging the Topological Pattern Analysis of Bitcoin Addresses in Blockchain Network for Ransomware Identification 1 Introduction 2 Objectives of the Study 3 Literature Review 4 Research Methodology 4.1 Statement of Problem 4.2 Research Design 4.3 Research Design 5 Data Analysis and Interpretation 5.1 Formulation of a Decision Tree Model for Classification 5.2 Formulation of a Random Forest Model for Classification 5.3 Formulation of a Binary Logistic Model for Classification 5.4 Formulation of a Multinomial Logistic Regression Model for Classification 6 Conclusion 7 Suggestions and Recommendations 8 Limitations References A Taxonomy and Survey of Software Bill of Materials (SBOM) Generation Approaches 1 Introduction 2 Software Bill of Materials 3 Literature Review 4 Outcome of the Review Process 5 Conclusion References Find Your Donor (FYD): An Algorithmic Approach Towards Empowering Lives and Innovating Healthcare 1 Introduction 2 Literature Survey/Previous Related Works 3 Proposed Methodology 3.1 Donor to Acceptor Matrix 3.2 Emergency Flag Mechanism 3.3 Architecture 4 Novelty/USP 5 Revenue Model 6 Risk and Mitigation Plan 7 Conclusion References Machine Learning, Deep Learning and Text Analytics Deep Learning-Based Multiple Detection Techniques of Covid-19 Disease From Chest X-Ray Images Using Advanced Image Processing Methods and Transfer Learning 1 Introduction 2 Related Works 3 Materials and Methods 3.1 Tools 3.2 The Datasets 3.3 Performance Parameters 3.4 Deep Neural Architecture 4 Experiments and Results 5 Conclusion References Classification Model to Predict the Outcome of an IPL Match 1 Introduction 2 Objectives of the Study 3 Literature Review 4 Research Methodology 5 Findings and Analysis 6 Model Evaluation and Output Interpretation 7 Validation 8 Conclusions 9 Future Scope of Research 10 Limitations References Knowledge Graph-Based Evaluation Metric for Conversational AI Systems: A Step Towards Quantifying Semantic Textual Similarity 1 Introduction 2 Literature Review 2.1 Wordnet 2.2 Overlap Systems 2.3 Semantic Analysis 2.4 Semantic Similarity Approach 2.5 Knowledge Based Approach 3 Methodology 3.1 Node Level Similarity 3.2 Entity Level Similarity 3.3 Relationship Level Similarity 3.4 Context Level Similarity 3.5 NERC Similarity Score 4 Benchmark Dataset used in Research 5 Experiments 6 Results 7 Conclusion References Are We Nearing Singularity? A Study of Language Capabilities of ChatGPT 1 Introduction 2 Language Complexity 2.1 Lexical Complexity 2.2 Syntactic Complexity 2.3 Semantic Complexity 3 Methods 4 Results 5 Discussion 6 Conclusion Appendix a: Sample Responses by ChatGPT References Thresholding Techniques Comparsion on Grayscale Image Segmentation 1 Introduction 2 Organisation of Paper 3 Image Thresholding 4 Threshold Selection 5 Various Thresholding Techniques 5.1 Percentile(P-tile)Thresholding 5.2 Mean Thresholding 5.3 Histogram Thresholding (HDT) 5.4 Edge Thresholding 5.5 Variable Thresholding 6 Experimental Results and Discussion 6.1 Tank Image 6.2 Couple Image 6.3 Girl Image 6.4 Plane Image 7 Applications of Image Segmentation 8 Conclusion References Automated Pneumonia Diagnosis from Chest X-rays Using Deep Learning Techniques 1 Introduction 1.1 Background and Motivation 1.2 Overview of Pneumonia 1.3 Importance of Early Diagnosis 1.4 Role of Computer Vision and Deep Learning 2 Problem Statement 2.1 Limitations of Traditional Pneumonia Diagnosis Methods 2.2 Need for Automated and Accurate Diagnosis 3 Objectives 4 Contributions 5 Literature Review 6 Methodology 6.1 Data Scrapping 6.2 Dataset Description 6.3 Deep Learning Architecture and Models 6.4 Hyper Parameter Tuning and Optimization 6.5 Performance Evaluation Metrics 7 Results 7.1 Convolutional Neural Network (CNN) 7.2 CNN with Hyper parameter Tuning 7.3 VGG16 7.4 ResNet50 7.5 DenseNet169 7.6 InceptionV3 8 Discussions 9 Discussion of New State-of-Arts Techniques 9.1 YOLO (You Only Look Once) 9.2 SAM (Spatial Attention Module) 9.3 Multi-modal Fusion 10 Conclusion References Detecting Emotional Impact on Young Minds Based on Web Page Text Classification Using Data Analytics and Machine Learning 1 Introduction 2 Background Research 3 Methodology 3.1 Data Collection 3.2 Data Cleaning 3.3 Data Pre-processing 3.4 Data Processing 3.5 One-Way ANOVA Test 4 Analysis and Results 5 Discussions 5.1 Contributions 6 Limitations and Future Research Scope 7 Conclusion Appendix A References Author Index