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检索条件"丛书名=Lecture Notes in Business Information Processing"

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Analyzing Customer Sentiments: A Comparative Evaluation of Large Language Models for Enhanced business Intelligence 1

引用

36th International Conference on Advanced information Systems Engineering (CAiSE)

作者： Beranek, Pavel Merunka, Vojtech Czech Univ Life Sci Fac Econ & Management Dept Informat Engn Prague Czech Republic Jan Evangelista Purkyne Univ Usti Nad Labem Sci Fac Dept Informat Usti Nad Labem Czech Republic Czech Univ Life Sci Prague Fac Econ & Management Dept Informat Engn Prague Czech Republic Czech Tech Univ Fac Nucl Sci & Phys Engn Dept Software Engn Prague Czech Republic

ISBN: (数字)9783031610035

ISBN: (纸本)9783031610028;9783031610035

This paper presents a comparative evaluation of Large Language Models (LLMs) against established sentiment analysis tools, focusing on their efficiency in parsing complex customer reviews for sentiment and emotion. Our research reveals that LLMs are capable of detecting a wide range of emotions, offering granular insights that transcend traditional analysis capabilities. However, the study also highlights a notable discrepancy in reproducibility and reliability among smaller LLMs (SLMs) when compared to the VADER model, a stalwart in sentiment analysis. These findings elucidate the potential and limitations of employing SLMs for business intelligence purposes, particularly in automating sentiment analysis of customer feedback. We discuss the implications of these outcomes for businesses looking to leverage AI for customer insights, emphasizing the importance of model selection based on the specific requirements of reproducibility and depth of analysis.

关键词： Large Language Models Small Language Models Sentiment Analysis Granular Sentiment Analysis Emotion Detection

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Error-Correcting Methodology for Evaluating Compliance to Clinical Guidelines: A Case Study on Rectal Cancer 5th

Error-Correcting Methodology for Evaluating Compliance to Cl...

引用

5th International Conference on Process Mining (ICPM)

作者： Savino, Mariachiara Fernandez-Llatas, Carlos Gatta, Roberto Chiloiro, Giuditta Di Franco, Silvia Ibanez-Sanchez, Gema Valero-Ramon, Zoe Gambacorta, Maria Antonietta Valentini, Vincenzo Damiani, Andrea Univ Cattolica Sacro Cuore Diagnost Immagini Radioterapia Oncolog & Ematol Rome Italy Univ Politecn Valencia SABIEN ITACA Valencia Spain Univ Brescia Dept Clin & Expt Sci Brescia Italy Fdn Policlin Univ Agostino Gemelli IRCC Diagnost Immagini Radioterapia Oncolog & Ematol Rome Italy Fdn Policlin Univ Agostino Gemelli IRCC Gemelli Generator Real World Data Rome Italy

ISBN: (纸本)9783031561061;9783031561078

In a clinical setting, physicians often need to tailor general clinical guidelines to match the specific characteristics of individual patients, resulting in deviations from the guidelines. Process mining provides a range of tools to evaluate how well patient pathways align with clinical guidelines. In this work we implement a novel conformance checking method that employs error-correcting techniques to provide a degree of deviation from the clinical guidelines. The described method allows the set of corrective actions to be defined interactively and the cost of each of them to be adjusted on the basis of clinical knowledge. We test the error-correction algorithm on a real-world cohort of locally advanced rectal cancer patients treated at Fondazione Policlinico Universitario A. Gemelli IRCCS to assess the degree of compliance to the European Society of Medical Oncology guidelines, translated into a computer-interpretable version with Pseudo-Workflow formalism. Using this approach, it is possible to extensively analyze the compliance of clinical treatments, from the control-flow to the data perspective, and to discover the most common types of deviations in our cohort.

关键词： Conformance Checking Rectal Cancer Process Mining Healthcare Error-Correcting Guidelines Compliance

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ExpO: Towards Explaining Ontology-Driven Conceptual Models 18th

ExpO: Towards Explaining Ontology-Driven Conceptual Models

引用

18th International Conference on Research Challenges in information Sciences (RCIS)

作者： Romanenko, Elena Calvanese, Diego Guizzardi, Giancarlo Free Univ Bozen Bolzano Bolzano Italy Umea Univ Umea Sweden Univ Twente Enschede Netherlands Stockholm Univ Stockholm Sweden

ISBN: (纸本)9783031594670;9783031594687

Ontology-driven conceptual models play an explanatory role in complex and critical domains. However, since those models may consist of a large number of elements, including concepts, relations and sub-diagrams, their reuse or adaptation requires significant efforts. While conceptual model engineers tend to be biased against the removal of information from the models, general users struggle to fully understand them. The paper describes ExpO-a prototype that addresses this tradeoff by providing three components: (1) an API that implements model transformations, (2) a software plugin aimed at modelers working with the language OntoUML, and (3) a web application for model exploration mostly designed for domain experts. We describe characteristics of every component and specify scenarios of possible usages.

关键词： Ontology-Driven Conceptual Models OntoUML Pragmatic explanation Software Tools

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Online Next Activity Prediction Under Concept Drifts 1

引用

36th International Conference on Advanced information Systems Engineering (CAiSE)

作者： Kosciuszek, Thaddeus Hassani, Marwan Eindhoven Univ Technol Eindhoven Netherlands

ISBN: (数字)9783031610035

ISBN: (纸本)9783031610028;9783031610035

Existing research in predictive process maintenance has recently focus on designing models for an online prediction where both training and testing should be performed efficiently, sequentially and in a scalable manner. However, less attention has been given to the realistic requirement of detecting concept drifts on the fly during training. Additionally, the retraining frequency as well as the training dataset size are used to be statically pre-decided. In this work, we address the previous shortcomings when designing our dynamic concept drift detection and online next activity prediction framework DynaTrainCDD. Our framework first uses a PrefixTree-driven method to detect drifts online then utilizes the Weibull distribution to estimate the retraining parameters. An extensive experimental evaluation using 10 real world datasets shows that our model additionally performs on par with or better than stateof-the-art methods in terms of accuracy while requiring a comparable running time.

关键词： Predictive Process Monitoring Concept Drift Detection

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Improving Understanding of Misinformation Campaigns with a Two-Stage Methodology Using Semantic Analysis of Fake News 18th

Improving Understanding of Misinformation Campaigns with a T...

引用

18th International Conference on Research Challenges in information Sciences (RCIS)

作者： Yameogo, Sidbewendin Angelique Univ Bretagne Sud Vannes France

ISBN: (纸本)9783031594670;9783031594687

Internet and social media are fueling the spread of disinformation on an unprecedented scale. Numerous tactics and techniques, such as Fake News, are employed to seek geopolitical advantages or financial gains. Many studies have focused on the automatic detection of Fake News, particularly using machine learning techniques. However, an informational attack often involves various vectors, targets, authors, and content. Detecting such an attack requires a global analysis of multiple Fake News instances. This research proposal aims to assist specialists, such as intelligence analysts or journalists responsible for combating disinformation, in better characterizing and detecting informational attacks. We propose a framework based on a two-stage approach. The first stage involves extracting valuable knowledge from each Fake News using both Artificial Intelligence and Natural Language processing (NLP) techniques. The second stage entails aggregating the collected information using data analysis methods to facilitate the characterization and identification of disinformation campaigns.

关键词： Disinformation Fake-news Analysis Conceptual Modeling

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Defining a Remote Work Policy: Aligning Actions and Intentions

Defining a Remote Work Policy: Aligning Actions and Intentio...

引用

24th International Conference on Agile Software Development (XP)

作者： Smite, Darja Moe, Nils Brede Blekinge Inst Technol Karlskrona Sweden SINTEF Digital Trondheim Norway

ISBN: (纸本)9783031485497;9783031485503

After the long period of forced work from home, many knowledge workers have not only developed a strong habit of remote work, but also consider flexibility as their personal right and no longer as a privilege. Existing research suggest that the majority prefers to work two or three days per week from home and are likely to quit or search for a new job if forced to return to full time office work. Given these changes, companies are challenged to alter their work policies and satisfy the employee demands to retain talents. The subsequent decrease in office presence, also calls for transformations in the offices, as the free space opens up opportunities for cutting the rental costs, as well as the other expenses related to office maintenance, amenities, and perks. In this paper, we report our findings from comparing work policies in three Nordic tech and fintech companies and identify the discrepancies in the way the corporate intentions are communicated to the employees. We discuss the need for a more systematic approach to setting the goals behind a revised work policy and aligning the intensions with the company's actions. Further, we discuss the need to resolve the inherent conflicts of interest between the individual employees (flexibility, individual productivity, and wellbeing) and the companies (profitability, quality of products and services, employee retention, attractiveness in the job market).

关键词： Flexible work policy Flexibility Remote work Work from home WFH Hybrid work Management Teams

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Enhancing Complex Linguistic Tasks Resolution Through Fine-Tuning LLMs, RAG and Knowledge Graphs (Short Paper) 1

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36th International Conference on Advanced information Systems Engineering (CAiSE)

作者： Bianchini, Filippo Calamo, Marco De Luzi, Francesca Macri, Mattia Mecella, Massimo Sapienza Univ Roma Dipartimento Ingn Informat Automat & Gest Antonio Rome Italy

ISBN: (数字)9783031610035

ISBN: (纸本)9783031610028;9783031610035

Given the synergy between Large Language Models (LLMs) and Knowledge Graphs (KGs), we introduce a pipeline to tackle complex linguistic tasks, which we are experimenting in the legal domain. While LLMs offer unprecedented generative capabilities, their reliance on sub-symbolic processing can lead to fallacious outcomes. Our methodology introduces an advanced Retrieval Augmented Generation (RAG) pipeline, enriched with two KGs and optimized LLMs, promising to enhance the resolution of complex linguistic tasks. Through KG construction based on prompt engineering techniques and iterative fine-tuning, we transcend the limitations of conventional LLMs.

关键词： Large Language Models Knowledge Graphs Complex linguistic tasks

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CaseID Detection for Process Mining: A Heuristic-Based Methodology 5th

CaseID Detection for Process Mining: A Heuristic-Based Metho...

引用

5th International Conference on Process Mining (ICPM)

作者： De Fazio, Roberta Balzanella, Antonio Marrone, Stefano Marulli, Fiammetta Verde, Laura Reccia, Vincenzo Valletta, Paolo Univ Campania Luigi Vanvitelli Dipartimento Matemat & Fis Viale Lincoln 7 Caserta Italy Gemat Srl Via Diocleziano 107 Naples Italy

ISBN: (纸本)9783031561061;9783031561078

Process Mining is getting a growing interest in many contexts where performance bottlenecks are critical for the business. Unfortunately, real cyber-physical systems are usually not implemented to easily address these techniques. One of the most frequent problems to face is transforming acquired data, often heterogeneous and unlabeled to allow the application of Process Mining technique. In this study, we propose an automatised and unsupervised methodology for extracting CaseIDs from an unlabeled event log. The proposed detection of CaseIDs is based on the definition of appropriate heuristic metrics, able to highlight the correlation between events that are part of the same process instance, according to temporal and topological features (e.g., kinds of functionally-related devices, topological distance, etc.). These features constitute the inputs for a clustering technique, which has been used to extract different cases. The performance of the proposed methodology was evaluated on a real diagnostic management system to support the decisions in maintenance operations in railway infrastructures. The system has been reproduced and tested in Gematica's laboratory for simulating the data used in this work.

关键词： Unlabeled Event Log CaseID detection Event Data K-Means Clustering Predictive Maintenance Railway Infrastructure

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Tiramisu: A Recipe for Visual Sensemaking of Multi-faceted Process information 5th

Tiramisu: A Recipe for Visual Sensemaking of Multi-faceted P...

引用

5th International Conference on Process Mining (ICPM)

作者： Alman, Anti Arleo, Alessio Beerepoot, Iris Burattin, Andrea Di Ciccio, Claudio Resinas, Manuel Univ Tartu Tartu Estonia TU Wien Vienna Austria Univ Utrecht Utrecht Netherlands Techn Univ Denmark Lyngby Denmark Sapienza Univ Rome Rome Italy Univ Seville Seville Spain

ISBN: (纸本)9783031561061;9783031561078

Knowledge-intensive processes represent a particularly challenging scenario for process mining. The flexibility that such processes allow constitutes a hurdle as it is hard to capture in a single model. To tackle this problem, multiple visual representations of the same processes could be beneficial, each addressing different information dimensions according to the specific needs and background knowledge of the concrete process workers and stakeholders. In this idea paper, we propose a novel framework leveraging visual analytics for the interactive visualization of multi-faceted process information, aimed at easing the investigation tasks of users in their process analysis tasks. This is primarily achieved by an interconnection of multiple visual layers, which allow our framework to display process information under different perspectives and to project these perspectives onto a domain-friendly representation of the context in which the process unfolds. We demonstrate the feasibility of the framework through its application in two use-case scenarios in the context of healthcare and personal information management.

关键词： Visual analytics Process mining Knowledge-intensive processes

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Navigating Remote Work: Challenges and Adaptations of Agile Teams Amidst Covid-19 25th

Navigating Remote Work: Challenges and Adaptations of Agile ...

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25th International Conference on Enterprise information Systems (ICEIS)

作者： Canedo, Edna Dias Calazans, Angelica Toffano Seidel Silva, Geovana Ramos Sousa Brito, Isabel Sofia Masson, Eloisa Toffano Seidel Univ Brasilia UnB Dept Comp Sci POB 4466 Brasilia DF Brazil Univ Ctr Brasilia UniCEUB BR-70910900 Brasilia DF Brazil Polytech Inst Beja Beja Portugal

ISBN: (纸本)9783031647475;9783031647482

Due to the COVID-19 pandemic, there was a massive migration from working in the office to working from home (WFH) and the software development teams had to adapt to the new reality. This paper focused on how the agile teams dealt with the challenges of WFH, face-to-face or hybrid during and after the Covid-19 pandemic and how this affected the software development process. To capture the perceptions of the agile teams, we carried out a survey that investigated the following aspects of WFH: work routine, collaboration, communication, productivity, transparency, challenges, and the software development process itself. The survey received 127 valid responses from agile team members and the results revealed that work continued normally during the pandemic, and there was a perception of increased effectiveness in productivity, communication, and interaction. To identify how agile teams adapted to post-pandemic hybrid work, we conducted a focus group to identify whether the changes implemented during the pandemic continued, which phases were most impacted, and which problems and practices were identified. The results showed that the most impacted phases of software development during and after the pandemic were Requirements Elicitation, Software Construction, and Project Management. Daily meeting was one of the most used practices during and after the pandemic. Clickup, Teams, E-mail, Whatsapp, Jira, Slack, and Google Meet tools were used during the pandemic and are still used to support hybrid work.

关键词： Working from home Agile software development Communication Productivity Interaction

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