Artificial Intelligence Applications and Innovations 20th IFIP WG 12.5 International Conference, AIAI 2024, Corfu, Greece, June 27–30, 2024, Proceedings, Part II

This book constitutes the refereed proceedings of the 20th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2024, held in Corfu, Greece, during June 27–30, 2024.

The 100 full papers and 8 short papers included in this book were carefully reviewed and selected from 213 submissions. The diverse nature of papers presented demonstrates the vitality of AI algorithms and approaches. It certainly proves the very wide range of AI applications as well.

.- AI-Driven Sentiment Trend Analysis: Enhancing Topic Modeling Interpretation with ChatGPT.
.- An algorithmic data pipeline architecture for the production of personalized telecom product offers.
.- Enhancing Financial Market Prediction with Reinforcement Learning and Ensemble Learning.
.- Generating Profiles of News Commentators with Language Models.
.- GreekT5: Sequence-to-Sequence Models for Greek News Summarization.
.- Improving RAG Quality for Large Language Models with Topic-Enhanced Reranking.
.- LLM Prompting versus  Fine-Tuning PLMs: A Comparative Study on Keyword Generation from Customer Feedback.
.- Multi-Dimensional Classification on Social Media Data for Detailed Reporting with Large Language Models.
.- Online Reinforcement Learning for Designing Automotive Hybrid Assembly Sequence: A Task Clustering-Guided Approach.
.- Strategizing the Shallows: Leveraging Multi-Agent Reinforcement Learning for Enhanced Tactical Decision-Making in Littoral Naval Warfare.
.- A Prediction Analysis for the Case of a Korean Police Dataset.
.- An AI-based Approach to Identify Financial Risks in Transportation Infrastructure Construction Projects.
.- Benign Paroxysmal Positional Vertigo disorders classification using eye tracking data.
.- Detecting Illicit Data Leaks on Android Smartphones Using an Artificial Intelligence Models.
.- Enhancing Predictive Process Monitoring with Conformal Prediction.
.- Improved NO2 Prediction using Machine Learning Algorithms.
.- Improving Agricultural Image Classification by Mining Images.
.- Learning-based Short-Term Energy Consumption Forecasting.
.- Machine learning models for electricity generation forecasting from a PV farm.
.- Pollutant concentration prediction by random forest to estimate a contaminant source position.
.- Predictive Maintenance under Absence of Sensor Data.
.- Simulation Study for evaluating efficiency of McPhail traps in olive groves.
.- SMT: Self-supervised approach for Multiple Animal Detection & Tracking.
.- The Impact of Augmentation Techniques on Icon Detection using Machine Learning Techniques.
.- Toward Unsupervised Energy Consumption Anomaly Detection.
.- Unlocking User Privacy: A Systematic Survey of Factors and Methods in Predicting App Permission Decisions.