Computational Collective Intelligence [electronic resource] : 16th International Conference, ICCCI 2024, Leipzig, Germany, September 9-11, 2024, Proceedings, Part I / edited by Ngoc Thanh Nguyen, Bogdan Franczyk, André Ludwig, Manuel Núñez, Jan Treur, Gottfried Vossen, Adrianna Kozierkiewicz.

-- Collective Intelligence and Collective Decision-Making. -- Collective Computational Intelligence - challenges and opportunities. -- Reward-based Hybrid Genetic Algorithm for Solving the Class Scheduling Problem. -- A Novel Multi-Criteria Approach Supporting Strong Sustainability Assessment. -- Enhancing Focused Ant Colony Optimization for Large-Scale Traveling Salesman Problems through Adaptive Parameter Tuning. -- Parallelized Population-based Multi-heuristic Approach for Solving RCPSP and MRCPSP Instances. -- A Collective Intelligence To Predict Stock Market Indices Applying An Optimized Hybrid Ensemble Learning Model. -- Deep Learning Techniques. -- Melanoma detection using CBR approach within a possibilistic framework. -- GANet - Learning tabular data using global attention. -- COVID-19 Detection based on Deep Features and SVM. -- Hybrid Convolutional Network Fusion: Enhanced Medical Image Classification with Dual-Pathway Learning from Raw and Enhanced Visual Features. -- Interpreting results of VGG-16 for COVID-19 diagnosis on CT images. -- A hybrid approach using 2D CNN and attention-based LSTM for Parkinson's Disease Detection from video. -- Improved CNN Model Stability and Robustness with Video Frame Segmentation. -- Deep Learning for Cardiac Diseases Classification. -- Natural Language Processing. -- BABot: a Framework for the LLM-based Chatbot Supporting Business Analytics in e-Commerce. -- BioBERT for Multiple knowledge-based question expansion and biomedical extractive question answering. -- AMAMP: A Two-Phase Adaptive Multi-hop Attention Message Passing Mechanism For Logical Reasoning Machine Reading Comprehension. -- Enhancing Low-Resource NER via Knowledge Transfer from LLM. -- Efficient Argument Classification with Compact Language Models and ChatGPT-4 Refinements. -- Refining Natural Language Inferences using Cross-Document Structure Theory. -- Data Mining and Machine Learning. -- Intelligent Handling of Noise in Federated Learning with Co-training for Enhanced Diagnostic Precision. -- Detection and Classification of olive leaves diseases using machine learning algorithms. -- Investigation of Machine Learning and Deep Learning Approaches for Early PM2.5 Forecasting: A Case Study in Vietnam. -- Detection of candidate skills from job offers and comparison with ESCO database. -- Multi-objective and Randomly Distributed Fuzzy Logic-based Unequal Clustering in Heterogeneous Wireless Sensor Networks. -- nMITP-Miner: An efficient method for mining frequent maximal inter-transaction patterns. -- A heterogeneous ensemble of classifiers for sports betting: based on the English Premier League. -- The New K-Means Initialization Method. -- Efficiently discover multi-level maximal high-utility patterns from hierarchical databases.

This two-volume set LNAI 14810-14811 constitutes the refereed proceedings of the 16th International Conference on Computational Collective Intelligence, ICCCI 2024, held in Leipzig, Germany, during September 9-11, 2024. The 59 revised full papers presented in these proceedings were carefully reviewed and selected from 234 submissions. They cover the following topics: Part I: Collective intelligence and collective decision-making; deep learning techniques; natural language processing; data mining and machine learning. Part II: Social networks and intelligent system; cybersecurity, blockchain technology, and internet of things; cooperative strategies for decision making and optimization; computational intelligence for digital content understanding; knowledge engineering and application for industry 4.0. .

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