Information Management and Big Data: 8th Annual International Conference, SIMBig 2021, Virtual Event, December 1–3, 2021, Proceedings (Communications in Computer and Information Science)

This book constitutes the refereed proceedings of the 8th International Conference on Information Management and Big Data, SIMBig 2021, held as a virtual event in December 2021. The 25 revised full papers and 2 revised short papers presented were carefully reviewed and selected from 67 submissions. The papers are organized in topical sections on data mining and applications; deep learning and applications; data-driven software engineering; health, NLP, and social media; image processing, machine learning, and semantic web. Preface Organization Contents Data Mining and Applications Automatic Data Imputation in Time Series Processing Using Neural Networks for Industry and Medical Datasets 1 Introduction 2 Related Work 2.1 Cui Chen and Chen MCNN 2.2 State-of-the-Art for Data Filling 3 Dataset 4 Experimental Setup 4.1 MCNN Baseline Model 4.2 LSTM Baseline Model 4.3 Our Approach for Automatic Imputation Model 5 Results 5.1 Classification 5.2 Regression 6 Conclusions and Future Work References Calibration of Traffic Simulations Using Simulated Annealing and GPS Navigation Records 1 Introduction 2 Background 2.1 SUMO and Traffic Simulations 2.2 Simulation Optimization Techniques 3 Solution Overview 3.1 Scenario Selection 3.2 Data Preparation from Waze 3.3 Calibration Algorithm Implementation 3.4 Calibration Algorithm 4 Results and Analysis 4.1 Calibration Results 4.2 Evaluation of Proposed Traffic Solutions 4.3 Sensitivity Analysis 5 Conclusions and Future Work References Predicting Daily Trends in the Lima Stock Exchange General Index Using Economic Indicators and Financial News Sentiments 1 Introduction 2 Materials and Methods 3 Experiments and Results 4 Conclusion References Government Public Services Presence Index Based on Open Data 1 Introduction 2 Related Work 3 Methodology 4 Experiments and Results 5 Conclusion References Clustering Analysis for Traffic Jam Detection for Intelligent Transportation System 1 Introduction 2 Related Works 3 Methodology 3.1 Data Preprocessing 3.2 Module OSMnx 3.3 Clustering Analysis 3.4 Visualization 4 Case Study and Results 4.1 Case Study 4.2 Experiments and Results 5 Discussion and Conclusions References Deep Learning and Applications A Study of Dynamic Convolutional Neural Network Technique for SCOTUS Legal Opinions Data Classification 1 Introduction 2 Related Work 3 Proposed Model 4 Experiments and Results 4.1 Dataset 4.2 Pre-processing 4.3 Experiments 5 Discussion 6 Conclusion References Hydra: Funding State Prediction for Kickstarter Technology Projects Using a Multimodal Deep Learning 1 Introduction 2 Related Works 3 Methodology 3.1 Business Understanding 3.2 Data Understanding 3.3 Data Preparation 3.4 Modeling 3.5 Evaluation 3.6 Deployment 4 Results 5 Conclusions References Composite Recommendations with Heterogeneous Graphs 1 Introduction 2 Related Work 3 Problem Statement 4 Proposed Approach 4.1 Generating a Heterogeneous Graph 4.2 Obtaining the Node Embeddings 4.3 Feature Aggregation 4.4 Composite Recommendations 5 Experimental Settings 5.1 Dataset 5.2 Graph Creation 5.3 Node Representations 5.4 Evaluation Metrics 5.5 Baseline 6 Experimental Results 6.1 Model's Performance 6.2 Effect of the Number of Similar Items (k) 6.3 Effect of the Embedding Dimension 6.4 Effect of the Random Walk Length 6.5 Effect of the Number of Random Walks 6.6 Effect of the Metapaths 7 Conclusions References Energy Efficiency Using IOTA Tangle for Greenhouse Agriculture 1 Introduction 2 Interplanetary Precision Agriculture Components 3 Material and Methods 3.1 Holonomic Autonomous Rover: Magrito 3.2 Precision Habitat PRO 3.3 Farm Management System 3.4 IOTA Private Tangle 3.5 Proposed Data Flow Towards IOTA Tangle 4 Theory and Calculation 4.1 Distributed Ledger Technologies 4.2 IOTA Streams and IOTA Channels 4.3 Machine-to-Machine Economy 4.4 Energy Consumption with IOTA Streams 5 Case Study: Astronaut Analog Mission 5.1 Space Analog Mission Protocols 6 Results 7 Discussion and Conclusion References Data-Driven Software Engineering Multiphase Model Based on K-means and Ant Colony Optimization to Solve the Capacitated Vehicle Routing Problem with Time Windows 1 Introduction 2 Related Work 3 Proposed Model 3.1 Phases of the Proposed Model 4 Validation 5 Results and Discussion 5.1 Phase 1: Order Scheduling 5.2 Phase 3: Delivery Routes Generation 5.3 Phase 4: Operator Assignment 6 Conclusions and Future Work References Enterprise Architecture Based on TOGAF for the Adaptation of Educational Institutions to e-Learning Using the DLPCA Methodology and Google Classroom 1 Introduction 2 Related Works 3 Proposed Model 3.1 Stage 1: Component Analysis 3.2 Stage 2: Design of the Proposal 3.3 Stage 3: Artifact Validation 4 Results and Discussion 5 Conclusions and Future Work References Quality Model for Educational Mobile Apps Based on SQuaRE and AHP 1 Introduction 2 Related Work 3 Proposed Quality Model 3.1 Quality Model Compilation 3.2 Unification of Characteristics and Sub-characteristics 3.3 Selection of Experts in Mobile Apps 3.4 Prioritizing Characteristics, Sub-characteristics and Metrics with AHP 3.5 Obtaining the Quality Model 4 Experimentation 4.1 Selection of Cases of Study 4.2 Experimental Definition and Planning 4.3 Execution of the Mobile App Assessment 4.4 Analysis of Results 5 Discussion 6 Conclusions and Future Work References Health, NLP, and Social Media Automatic Detection of Levels of Intimate Partner Violence Against Women with Natural Language Processing Using Machine Learning and Deep Learning Techniques 1 Introduction 2 Related Work 3 Methodology 3.1 Database 3.2 Preprocessing 3.3 Feature Extraction 3.4 Modeling 3.5 Model Evaluation 4 Results 5 Conclusions and Recommendations References Deep Learning vs Compression-Based vs Traditional Machine Learning Classifiers to Detect Hadith Authenticity 1 Introduction 2 Related Work 3 Proposed Data Sets 3.1 Non-authentic Hadith (NAH) Corpus 3.2 Leeds University and King Saud University (LK) Hadith Corpus 4 Deep Learning Classifiers 5 Experiments and Results 5.1 Authentication Based on Hadith 5.2 Authentication Based on Isnad 5.3 Authentication Based on Matan 6 Conclusion References Classical Machine Learning vs Deep Learning for Detecting Cyber-Violence in Social Media 1 Introduction 2 Related Works 2.1 Classical ML 2.2 DL Techniques 3 Approach and Method 3.1 Features Extraction 3.2 ML Algorithms 4 Evaluation 4.1 Materials 4.2 Experiments 4.3 Results and Discussion 5 Conclusion References Automatic Detection of Deaths from Social Networking Sites 1 Introduction 2 Related Work 2.1 SNSs as Platforms for Grieving and Memorialising the Dead 2.2 NLP Methods for Detection of Deaths 3 Methodology 3.1 Data Collection and Annotation 3.2 Pre-processing 3.3 Text Representation and Classification 3.4 Analysis of Linguistic Characteristics and Practices 4 Evaluation 4.1 Inter-annotator Agreement 4.2 Classification of Pre- and Post-mortem Contents 4.3 Analysis of Linguistic Characteristics and Practices 5 Conclusion 6 Future Work References Model Comparison for the Classification of Comments Containing Suicidal Traits from Reddit via NLP and Supervised Learning 1 Introduction 2 State of the Art 3 Background 3.1 SuicideWatch 3.2 TF-IDF 3.3 Glove 4 Methodology 5 Experimentation 5.1 Compiling, Loading and Data Cleaning 5.2 Feature Extraction 5.3 Classification Models 6 Results 7 Discussion References A Data-Driven Score Model to Assess Online News Articles in Event-Based Surveillance System 1 Introduction 2 State of the Art 3 Proposed Work 3.1 Data Quality Measures (DQM) 4 Evaluation 4.1 Dataset 4.2 Results 5 Discussion 6 Conclusion References AmLDA: A Non-VAE Neural Topic Model 1 Introduction 2 Previous Work 2.1 Latent Dirichlet Allocation (LDA) 2.2 VEM, SVI, and VAE for LDA 3 Method 4 Experiment 4.1 Datasets and Implementation Details 4.2 Evaluation Results 5 Conclusions References Auditing Algorithms: Determining Ethical Parameters of Algorithmic Decision-Making Systems in Healthcare 1 Introduction 1.1 Motivation 2 Related Work 2.1 Post-hoc Interpretability Tools to Audit AI Models 2.2 AI Fairness Models to Mitigate Bias 2.3 Data Visualization Models to Discern Differences 3 Dataset 3.1 Data Preparation 4 Models of Analysis 4.1 Lime for Model Auditing 4.2 AIF360 Model Analysis 4.3 Data Triangulation 5 Model Evaluation 5.1 LIME Model Evaluation 5.2 AIF360 Model Evaluation 5.3 Data Triangulation Evaluation 6 Conclusion and Future Work References Image Processing, Machine Learning, and Semantic Web Plant Disease Classification and Severity Estimation: A Comparative Study of Multitask Convolutional Neural Networks and First Order Optimizers 1 Introduction 2 Related Works 3 Methodology 3.1 Dataset 3.2 Environment Setup 3.3 Deep Learning Architectures 3.4 Deep Learning Optimizers 3.5 Training Specifications 4 Results 5 Discussion 6 Conclusion References Crack Detection in Oil Paintings Using Morphological Filters and K-SVD Algorithm 1 Introduction 2 Digital Analysis of Art 2.1 Approaches in the Spatial Domain 2.2 Approaches in the Frequency Domain 2.3 Feature Extraction Algorithms 3 Method for Crack Detection 3.1 Image Pre-processing 3.2 Crack Detection 3.3 Post-processing 3.4 Voting Scheme 4 Experimental Setup 4.1 Dataset 4.2 Parameters 4.3 Crack Detection 5 Discussion 6 Conclusion References CoffeeSE: Interpretable Transfer Learning Method for Estimating the Severity of Coffee Rust 1 Introduction 2 Background Concepts 2.1 Color Spaces 2.2 Color-Based Segmentation 2.3 Transfer Learning 3 Proposed Method 3.1 Leaf Segmentation 3.2 Patch Sampling 3.3 Patch-Based Classification 3.4 Quantification and Interpretation Analysis 4 Experiments 4.1 Coffee Leaves Datasets 4.2 Leaf Segmentation 4.3 Sørensen Similarity Index 4.4 Patch Classifier Interpretability Module 5 Conclusions and Future Works References Investigating Generative Neural-Network Models for Building Pest Insect Detectors in Sticky Trap Images for the Peruvian Horticulture 1 Introduction 2 Materials and Methods 2.1 Data Collection and Pre-processing 2.2 Generative Models 2.3 Generation of Sticky Trap Images 2.4 Detection with YOLOv5 3 Results and Discussion 3.1 Performance Evaluation of Pest Insect Image Synthesis 3.2 Evaluation of Pest Insect Detection and Classification 4 Conclusion References Making Licensing of Content and Data Explicit with Semantics and Blockchain 1 Introduction 2 Problem Statement 2.1 Functional Requirements 2.2 Non-functional Requirements 3 Implementation 3.1 Technology Choices 3.2 Backend and Frontend 4 Evaluation 5 Conclusion References Deep Neural Networks Based Solar Flare Prediction Using Compressed Full-disk Line-of-sight Magnetograms 1 Introduction 2 Related Work 3 Data Preparation 4 Model Architecture 5 Experimental Evaluation 5.1 Experimental Settings 5.2 Evaluation 6 Conclusion and Discussion References Prediction of Soil Saturated Electrical Conductivity by Statistical Learning 1 Introduction 2 Related Work 3 Methodology 3.1 Dataset Description, Pre-processing and Exploratory Analysis 3.2 Modelling 3.3 Goodness of Fit Measures 4 Results and Discussion 4.1 Data Preprocess and Exploratory Analysis 4.2 Multiple Linear Regression 4.3 Generalized Additive Models 4.4 Bayesian Additive Regression Trees 4.5 Extreme Gradient Boosting Trees 4.6 Neural Network 4.7 Models Comparison 5 Conclusions References Author Index