Full Description
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.
Contents
.- 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.
