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Multi-dimensional Classification on Social Media Data for Detailed Reporting with Large Language Models 1

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20th International Conference on Artificial Intelligence Applications and Innovations (AIAI)

作者： Cantini, Riccardo Cosentino, Cristian Marozzo, Fabrizio Univ Calabria Arcavacata Di Rende CS Italy

ISBN: (数字)9783031632150

ISBN: (纸本)9783031632174;9783031632150;9783031632143

Every day, more and more people harness the power of social media platforms to express their thoughts, share information and personal experiences, and 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 based on dimensions such as topic, sentiment, and emotion, it is possible to create even more detailed reports by carefully condensing large amounts of data collected along the different dimensions considered. To tackle this challenge, we have developed an automated approach with two primary goals: (i) categorizing posts across different dimensions using ready-to-use and fine-tuned classifiers;and (ii) generating detailed reports via LLMs that summarize posts with similar characteristics along the defined dimensions. In our analysis, we examined a large and varied set of posts about COVID, classifying them along several dimensions, including topic, content type, expressed sentiment and emotions, and reliability of information. Specifically, by choosing to generate a report for the main discussion topics present in the dataset, such as allergic reactions or school issues, and using the remaining dimensions for post classification, we successfully created highly detailed and informative reports with ChatGPT. These reports outperformed those generated directly by ChatGPT, in both quantitative measures such as linguistic scores and qualitative evaluations by field experts.

关键词： Large Language Models Deep Learning Natural Language Processing ChatGPT Social media data Reporting

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Snowed In and Cut Off: How a Norwegian Municipality Dealt with a Power Outage 8th

Snowed In and Cut Off: How a Norwegian Municipality Dealt wi...

引用

8th International Conference on information technology in Disaster Risk Reduction (ITDRR)

作者： Rustenberg, Kjetil Steen-Tveit, Kristine Univ Agder Ctr Integrated Emergency Management CIEM Kristiansand Norway

ISBN: (纸本)9783031640391;9783031640377;9783031640360

This case study investigates the impact of interaction and information-sharing challenges between a small Norwegian municipality and other Emergency Response organisations during a power outage. We explore how these challenges relate to time and the different phases of the disaster management life cycle. Through interviews and surveys involving various stakeholders, our findings point to deficiencies in notification and engagement among essential resources. These issues led to notification and engagement problems that hampered the municipality's involvement. Our study identifies organisational boundaries and emphasises the potential improvements that operational procedures and action cards can bring to communication, information sharing, and role understanding in similar scenarios. We contend that examining such events through the lens of information Trading Zones (TZ) offers valuable insights into how collaborative efforts can enhance Team Situational Awareness (TSA) and foster a common operational picture (COP).

关键词： Preparedness procedures operationalisation situational awareness

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Personal Data Sovereignty in Virtual Enterprises: Implementing Data Capsules for Enhanced Privacy and Compliance 25th

Personal Data Sovereignty in Virtual Enterprises: Implementi...

引用

25th ifip WG 5.5 Working Conference on Virtual Enterprises (PRO-VE)

作者： Baraku, Vijon Paraskakis, Iraklis Veloudis, Simeon Yadav, Poonam Univ York Dept Comp Sci York England SEERC South East European Res Ctr Thessaloniki Greece CITY Coll Univ York Europe Campus Thessaloniki Greece

ISBN: (纸本)9783031717413;9783031717390;9783031717383

In the context of Virtual Enterprises (VEs), the intersection between big data analytics, data ownership, and regulatory compliance raises significant challenges. This paper presents a novel framework for redefining data control within VEs by transferring ownership from Data Controller entities to individuals. Central to this framework is the proposed novel notion of the Data Capsule, which empowers individuals with personal data sovereignty i.e., with the ability to dictate the terms and conditions of their data usage directly. The Data Capsule system leverages ontologies, semantic technologies, and blockchain to homogenise heterogeneous data, enable annotation, enforce governance rules, and assure transparency. This framework addresses the unique data management needs of VEs by promoting transparency and allowing all participants to openly state the level and type of engagement permitted with their data. By making individuals the primary custodians of their data, this paper intends to enhance privacy, security, and ethical data handling while avoiding the possible drawbacks of profit-driven approaches. The paper additionally considers compliance with pertinent legislation including the European Union's General Data Protection Regulation (GDPR), the Data Governance Act and the AI Act. The suggested framework provides considerable benefits to SMEs in VEs, such as competitive advantage and cost savings. This paper outlines a research plan, provides a state-of-the-art analysis, establishes the system's objectives, and aligns the framework with the needs of VEs.

关键词： Data Sovereignty Data Ownership Data Privacy Virtual Enterprises Ontologies Blockchain technology GDPR

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Life Cycle Analysis for the Concept Design of a Smart Mobile Factory (SMF) for Infrastructure Construction Projects 43rd

Life Cycle Analysis for the Concept Design of a Smart Mobile...

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43rd ifip WG 5.7 International Conference on advances in Production Management Systems (APMS)

作者： Dallasega, Patrick Kaushal, Ishaan Revolti, Andrea Miori, Nicholas Free Univ Bozen Bolzano Fac Engn Piazza Domenicani 3 I-39100 Bolzano Italy

ISBN: (纸本)9783031716393;9783031716379;9783031716362

This research paper investigates the environmental implications of an innovative concept of a Smart Mobile Factory (SMF) for infrastructure construction projects. The paper is part of the research project Smart Mobile Factory for infrastructure projects (SMF4INFRA). Traditionally, the prefabrication is organized in a centralized manner in fixed factories, with big lot sizes and long lead times. Specifically, in the case of linear infrastructure construction projects, where the construction site needs to move as the construction progresses, centralized manufacturing creates high environmental impacts. The SMF is a mobile manufacturing unit that moves with the construction site, thereby reducing transportation distances and associated environmental impacts. The study compares three different SMF variants - concrete-based, wood-based, and pneumatic-based - in the context of a hyperloop track construction between Zurich and Geneva (CH). The Life Cycle Assessment (LCA) method is employed to evaluate and compare the environmental impacts of these three variants. The results indicate that the pneumatic-based SMF variant has the least environmental impact when considering factors such as transportation, assembly, disassembly, and the materials used in the components of the SMF. The paper concludes by suggesting future research directions. It proposes the development of a dynamic LCA that includes the operations of SMF to produce, transport and install hyperloop tubes. Furthermore, it recommends integrating this system into a Digital Twin environment for improved monitoring and control of the environmental impacts.

关键词： Life Cycle Assessment Mobile Factory Distributed Manufacturing Construction Digital Factory

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A Constraint-Based Greedy-Local-Global Search for the Warehouse Location Problem 20th

A Constraint-Based Greedy-Local-Global Search for the Wareho...

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20th International Conference on Artificial Intelligence Applications and Innovations (AIAI)

作者： Loeffler, Sven Hofstedt, Petra Brandenburg Univ Technol Cottbus Senftenberg Konrad Wachsmann Allee 5 D-03046 Cottbus Germany

ISBN: (纸本)9783031632211;9783031632198;9783031632181

Constraint optimization problems offer a means to obtain a global solution for a given problem. At the same time the promise of finding a global solution often comes at the cost of significant time and computational resources. In contrast, greedy search and local search represent two alternative approaches, which can lead fast to local optima. In this paper, we explore the advantages of incorporating greedy search and local search into constraint optimization methods without forsaking the pursuit of a global solution. The different instances of our global search process are designed to initially behave akin to a greedy search and a local search while they are integrated in a global search approach. This dual strategy aims to achieve two key objectives: firstly, it accelerates the attainment of an initial solution, and secondly, it ensures that this solution possesses a high level of optimality. Even though constraint programming theoretically finds a global optimum, in practice, this may not always be the case due to time and hardware limitations. Our approach improves upon the general Branch-and-Bound approach in constraint programming, aiming to find a good or optimal solution faster than the conventional method. Finally, we validate our findings using the warehouse location problem as a case study.

关键词： Planning and Scheduling Constraint Programming Greedy Search Local Search Global Search Warehouse Location Problem

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French-Style Applications of Artificial Intelligence to Human Health in a European Context 16th

French-Style Applications of Artificial Intelligence to Huma...

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16th ifip International Conference on Human Choice and Computers (HCC)

作者： Desbois, Dominique INRAE AgroParis Tech Paris Saclay Appl Econ 22 Pl AgronCS 20040 F-91123 Palaiseau France

ISBN: (纸本)9783031675379;9783031675355;9783031675348

In this paper, we discuss the applications of artificial intelligence to human health and the problems this poses in France. We explore the field of application of weak artificial intelligence to human health problems in relation to questions of socio-economic development, law and ethics. We also look at issues arising from strong Artificial Intelligence. We present a few examples of applications of weak artificial intelligence in various fields: predictive medicine, precision medicine, diagnostic and therapeutic assistance, supportive care, computer-assisted surgery, epidemic prevention and pharmacovigilance, and access to care. Within the European regulatory context of the single digital market and the personal data protection regulation, we illustrate the societal issues surrounding the application of artificial intelligence. We conclude with the prospects for the development of artificial intelligence applications in human health in France within a European context.

关键词： Artificial Intelligence Human Health France Europe

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LLM Prompting Versus Fine-Tuning PLMs: A Comparative Study on Keyword Generation from Customer Feedback 1

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20th International Conference on Artificial Intelligence Applications and Innovations (AIAI)

作者： Er, Aleyna Diri, Banu Yondem, Meltem Turhan Yildiz Tech Uni Dept Comp Engn Istanbul Turkiye SeturTech IT & R&D Ctr Istanbul Turkiye

ISBN: (数字)9783031632150

ISBN: (纸本)9783031632174;9783031632150;9783031632143

This study focuses on keyword generation of customer feedback analysis within the tourism sector regarding tour and hotel services provided by Setur. A dataset comprising 1000 customer surveys from 2020-2022 was crafted by annotating keywords gleaned from open-ended questions. The research employs the efficacy of fine-tuning Pre-trained Language Models (PLMs) and employing Large Language Models (LLMs) through prompting for keyword generation. The study navigates through traditional statistical methods, such as TF-IDF and KP-MINER, and contemporary approaches, such as YAKE, PageRank, and TextRank. Additionally, it explores supervised methodologies, including KEA and sequence-to-sequence models, juxtaposed against the surge in popularity of pre-trained language models like T5, Bart, GPT3.5, GPT4, and Gemini. In our experimental approach, multilingual versions of T5 and Bart models, namely MT5 and MBART, were fine-tuned to prior studies. Comparison extended to include GPT3.5, GPT4, and Gemini models, utilizing diverse prompt styles, and introducing few-shot examples to discern changes in performance. The semantic similarity evaluations between generated keywords and the source text, text length metrics, and inter-keyword semantic similarity are presented. Along with MBART and MT5, Turkish language models TRBART and TRT5 were employed. The study not only aims to contribute insights into the domain of customer feedback analysis but also to serve as a benchmark for comparing the efficiency of PLM fine-tuning and LLM prompting in keyword generation from textual data.

关键词： Customer Feedback Keyword Generation Pre-trained Language Models Large Language Models Tourism Natural Language Processing

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Towards a Conceptual Model for Enhancing Efficiency and Collaboration in Agile Ramp-Up Projects Planning 25th

Towards a Conceptual Model for Enhancing Efficiency and Coll...

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25th ifip WG 5.5 Working Conference on Virtual Enterprises (PRO-VE)

作者： Jarrar, Qussay Taleb, Cheikh S-A-M Kadkhoda-Ahmadi, Shervin Medini, Khaled Univ Clermont CNRS INOP Clermont Auvergne Mines St EtienneUMR LIMOS 6158 F-42023 St Etienne France

ISBN: (纸本)9783031717413;9783031717390;9783031717383

Agility is a major concern for industries across manufacturing and service sectors for a variety of reasons. For instance, frequent product development to meet evolving customer requirements and changing markets requires efficient and agile processes. Therefore, companies need to capitalize on product and service development and ramp-up projects in order to improve their efficiency as well as time-to-market. This paper provides preliminary results to address this gap by proposing a model covering conceptual underpinnings of agile ramp-up management. The model is developed iteratively following the design science research methodology. A simple excel prototype resulting from the model is developed in order to support agile ramp-up project planning. The model as well as the prototype are expected to help decision makers in scoping ramp-up projects and in improving the consistency of these projects planning. They also support the collaboration within ramp-up project team through sharing a common understanding of the project scope.

关键词： Ramp-up projects conceptual model innovation collaboration

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Do There Exist an Emotion Trend in Scientific Papers? PRO-VE Conference as a Case 25th

Do There Exist an Emotion Trend in Scientific Papers? PRO-VE...

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25th ifip WG 5.5 Working Conference on Virtual Enterprises (PRO-VE)

作者： Venumuddala, Rishitha Xu, Lai de Vrieze, Paul Bournemouth Univ Dept Comp & Informat Bournemouth BH12 5BB Dorset England

ISBN: (纸本)9783031717413;9783031717390;9783031717383

Scientific writing aims for formality and objectivity, yet emotions are integral to human communication, decision-making, and collaboration, all of which are fundamental to scientific progress. Existing research on emotion detection has mainly focused on datasets from social media and online platforms, where emotional expressions are abundant. However, scientific texts pose unique challenges due to their formal language and the rarity of explicit emotional words, necessitating specialised investigation. This study investigates the presence and nature of emotions in scientific texts, specifically analysing the abstracts from the PRO-VE conference series from 2012 to 2022. Two emotion detection methods are employed: a lexicon-based approach and a hybrid machine learning-based approach. The lexicon-based approach utilises the NRC Emotion Lexicon to identify and quantify emotions within the PRO-VE abstracts, while the hybrid approach integrates Word2Vec for word embedding generation and a Random Forest classifier for emotion prediction. The findings reveal a predominance of positive emotions, such as trust, anticipation, and joy, in the PRO-VE abstracts, consistent with the objective nature of scientific writing. In light of the PRO-VE conference series' 25th anniversary, an analysis of trends and patterns in the detected emotions offers insights into the emotional landscape of this prestigious conference series. The study also critically examines the limitations of the experiments, including the dataset size and the prevalence of positive emotions.

关键词： Emotion Detection PRO-VE Emotion in Collaborative Networks Emotion Trend in Collaborative Networks Collaborative Networks

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Smart-Grid-Enabled Business Cases and the Consequences of Cyber Attacks 17th

Smart-Grid-Enabled Business Cases and the Consequences of Cy...

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17th Critical Infrastructure Protection

作者： Toftegaard, Oyvind Abraham, Doney Shenoi, Sujeet Hammerli, Bernhard Norwegian Energy Regulatory Author Oslo Norway Norwegian Univ Sci & Technol Gjovik Norway Univ Tulsa Tulsa OK USA Lucerne Univ Appl Sci & Arts Luzern Switzerland

ISBN: (纸本)9783031495878;9783031495854;9783031495847

The introduction of smart metering systems is a paradigm shift for the power grid. New business cases such as virtual power plants and local flexibility markets are evolving. Security risks and the potential consequences of smart-grid-enabled business cases have been assessed by researchers. However, the research efforts have not ranked the business cases according to their potential disruptive consequences, which makes it difficult to prioritize risk reduction measures. This chapter describes the results of a survey of market players that sought to rank smart-grid-enabled business cases based on their perceptions of cyber attack consequences. As expected, the consequence perceptions of the market players vary considerably between the business cases. Consequence scenarios suggested by the market players are employed to explain the highest-ranked business cases, which include digital twins, remote access to smart meter circuit breakers, and grid flexibility and balance management. The survey results can support governments and market players in assessing power grid risk and prioritizing risk reduction measures.

关键词： Smart Grids Business Cases Cyber Attacks Consequences

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