Titlebook: Artificial Intelligence Applications and Innovations; 20th IFIP WG 12.5 In Ilias Maglogiannis,Lazaros Iliadis,Antonios Papale Conference pr

parsimony

AI-Driven Sentiment Trend Analysis: Enhancing Topic Modeling Interpretation with ChatGPTiment analysis and topic modeling, extracting meaningful insights from the vast amount of textual data generated on social media platforms presents unique challenges due to the short and noisy nature of the text. In this study, we propose a methodology for analyzing sentiment trends in social media,

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An Algorithmic Data Pipeline Architecture for the Production of Personalized Telecom Product Offerst” product at the “best” price, choosing from an increasingly complex collection of offers and tariff packages. To this end, various methods are aiming to understand and estimate the user‘s behavior, predict traffic and willingness to pay. Based on such information, sales channels select and propose

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nuclear-tests

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HAIRY

unstable-angina

Multi-dimensional Classification on Social Media Data for Detailed Reporting with Large Language Mod engage with others. All this knowledge can then be transformed into informative reports with the assistance of Large Language Models (LLMs), like ChatGPT, which leverage deep learning techniques to analyze data and generate comprehensive analyses. By effectively classifying user-generated posts bas

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Entirety

Strategizing the Shallows: Leveraging Multi-Agent Reinforcement Learning for Enhanced Tactical Deciscal evidence. These conflicts are well-represented within the framework of Partially Observable Stochastic Games (POSG), which models the adversarial interactions between contending forces through decision-making agents, possible states, actions, observations, and probabilistic state transitions..Th