Computational Collective Intelligence

16th International Conference, ICCCI 2024, Leipzig, Germany, September 9-11, 2024, Proceedings, Part I
Herausgegeben:Nguyen, Ngoc Thanh; Franczyk, Bogdan; Ludwig, André; Núñez, Manuel; Treur, Jan; Vossen, Gottfried; Kozierkiewicz, Adrianna

• Broschiertes Buch

Produktbeschreibung

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.

Produktdetails

• Lecture Notes in Computer Science 14810
• Verlag: Springer / Springer Nature Switzerland / Springer, Berlin
• Artikelnr. des Verlages: 978-3-031-70815-2
• 2024
• Seitenzahl: 428
• Erscheinungstermin: 6. September 2024
• Englisch
• Abmessung: 235mm x 155mm x 24mm
• Gewicht: 645g
• ISBN-13: 9783031708152
• ISBN-10: 3031708156
• Artikelnr.: 71278397

Inhaltsangabe

.- 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.