Advances in Computational Collective Intelligence [electronic resource] : 15th International Conference, ICCCI 2023, Budapest, Hungary, September 27–29, 2023, Proceedings /

Collective Intelligence and Collective Decision-Making -- Assessing the Effects of Expanded Input Elicitation and Machine Learning-based Priming for Crowd Stock Prediction -- RaReSi: An Approach Combining Ratings and Reviews to Measure User Similarity in Neighbor-based Recommender Systems -- Personalized Quiz-Based Perfume Recommender System Using Social Data -- LSTM-based QoE Evaluation for Web Microservices’ Reputation Scoring -- Previous Opinions is All You Need - Legal Information Retrieval System -- An Agent-Based Network Model for Interpersonal Emotion Regulation in Human-Bot Interaction -- Deep Learning Techniques -- Optimizing Deep Learning for Computer-Aided Diagnosis of Lung Diseases: An Automated Method Combining Evolutionary Algorithm and Transfer Learning -- Deep Bidirectional LSTM Network Learning-Based Sentiment Analysis for Tunisian Dialectical Facebook Content during the Spread of the Coronavirus Pandemic -- Interpretation of immunofluorescence slides by Deep Learning techniques: Anti-nuclear antibodies case study -- An improved approach for Parkinson’s disease classification based on convolutional neural network -- A Convolutional Recurrent Neural Network model for Classification of Parkinson’s Disease from Resting State EEG signals -- Recognition of Alzheimer’s Disease based on Transfer Learning Approach using Brain MRI Images With Regularization -- Detection and analyzing satellite images by using Conventional neural network -- Classifying Chicken-Made Food Images Using Enhanced MobilNetV2 -- Natural Language Processing -- Initial approach to pharmaceutical opinion search in polish language -- WSDTN a novel dataset for Arabic word sense disambiguation -- CNN-BiLSTM model for Arabic Dialect Identification -- Active Learning with AraGPT2 for Arabic Named Entity Recognition -- FreMPhone: A French Mobile Phone Corpus for Aspect-based Sentiment Analysis -- OTSummarizer an Optimal Transport based approach for extractive text summarization -- Towards a hybrid document indexing approach for Arabic documentary retrieval system -- Sh-DistilBERT: new transfer learning model for Arabic Sentiment Analysis and Aspect Category Detection -- Data Minning and Machine learning -- A hybrid method of k-nearest neighbors with decision tree for water quality classification in aquaculture -- Evaluating Web Crawlers with Machine Learning Algorithms for Accurate Location Extraction from Job Offers -- A Design Science Research Approach Towards Knowledge Discovery and Predictive Maintenance of MEMS Inertial Sensors Using Machine Learning -- Efficient Pruning Strategy for Mining High Utility Quantitative Itemsets -- AAPL forecasting using contemporary time series models -- Improving Gossip Learning via Limited Model Merging -- Ensemble Machine Learning-Based Egg Parasitism Identification for Endangered Bird Conservation -- Social Networks and Speek Communication -- A Comparative Analysis of Long Covid in the French Press and Twitter -- Semantic analysis of transit related tweets in London and Prague -- k-shell Without Decomposition -- Difficulties developing a children’s speech recognition system for languages with limited training data -- Kazakh-Uzbek Speech Cascade Machine Translation on Complete Set of Endings -- Cybersecurity and Internet of Things -- Human-related security threats and countermeasures of electronic banking and identity services - Polish case study -- Design and Development of IoT based Medical Cleanroom -- Reliable framework for Digital Forensics in Medical Internet of Things -- Federated Learning - Opportunities and Application Challenges -- Cooperative Strategies for Decision Making and Optimization -- A new Ant population based improvement heuristic for solving large scale TSP -- Comparison of various mutation operators of the bacterial memetic algorithm on the traveling salesman problem -- Comparing Lamarckian and Baldwinian Approaches in Memetic Optimization -- A Fitness Approximation Assisted Hyper-heuristic for the Permutation Flowshop Problem -- Generalized objective function to ensure robust evaluation for evolutionary storage location assignment algorithms -- Bacterial Evolutionary Algorithm based Autoencoder Architecture Search for Anomaly Detection -- Digital Content Understanding and Apllication for Industry 4.0 -- Improved Object Detection by Utilizing the Image Stream -- Combination of DE-GAN With CNN-LSTM for Arabic OCR on Images with Colorful Backgrounds -- A Solution for Building a V-Museum Based on Virtual Reality Application -- Synthetic football sprite animations learned across the pitch -- Solving the Hydrophobic-Polar model with Nested Monte Carlo Search -- Ground Truth Data Generator In Automotive Infrared Sensor Vision Problems Using a Minimum Set of Operations -- Theoretical and empirical testing of the randomness of a quantum random number generator with quantum entanglement -- Computational Intelligence in Medical Applications -- Robust Brain Age Estimation via Regression Models and MRI-derived Features -- Efficient Analysis of Patient Length of Stay in Hospitals Using Classification and Clustering Approaches. Electrocardiogram-based Heart Disease Classification with Machine Learning Techniques -- SS-FL: Self-Supervised Federated Learning for COVID-19 Detection from Chest X-ray Images -- A New Approach For The Diagnosis of Children Personality Disorders Based On Semantic Analysis -- Comparative Analysis of Human Action Recognition Classification for Ambient Assisted Living -- Overview of Time Series Classification based on symbolic discretization for ECG applications -- Res 1D CNN and BiLSTM with Attention Mechanism Integration for Arrhythmia Diagnosis.

This book constitutes the refereed proceedings of the 15th International Conference on Advances in Computational Collective Intelligence, ICCCI 2023, held in Budapest, Hungary, during September 27–29, 2023. The 59 full papers included in this book were carefully reviewed and selected from 218 submissions. They were organized in topical sections as follows: Collective Intelligence and Collective Decision-Making, Deep Learning Techniques, Natural Language Processing, Data Minning and Machine learning, Social Networks and Speek Communication, Cybersecurity and Internet of Things, Cooperative Strategies for Decision Making and Optimization, Digital Content Understanding and Apllication for Industry 4.0 and Computational Intelligence in Medical Applications.