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Domain TILEs: Test Informed Learning with Examples from the Testing Domain 17th

Domain TILEs: Test Informed Learning with Examples from th...

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17th International Conference on Research Challenges in information Sciences, RCIS 2023

作者： Doorn, Niels Vos, Tanja Marín, Beatriz Bockisch, Christoph Dick, Steffen Barendsen, Erik Open Universiteit Heerlen Netherlands Universitat Politècnica de València Valencia Spain Philipps-Universität Marburg Germany

ISBN: (纸本)9783031330797

Test Informed Learning with Examples (TILE) helps educators to add testing to their programming courses early, easily and in a subtle way. Currently, TILE describes how to add informed examples of testing to test runs, test cases, and messages. In this paper, we extend TILE by incorporating information from the testing domain itself into the examples. Our non-conclusive results from a survey with 300 participants indicate that using TILE, results in students creating more tests that cover more parts of the code. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Software testing

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Realising Fair Outcomes from Algorithm-Enabled Decision Systems: An Exploratory Case Study 1

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11th International Workshop on Enterprise Applications, Markets and Services in the Finance Industry, FinanceCom 2022

作者： Koefer, Franziska Lemken, Ivo Pauls, Jan University of Twente Enschede Netherlands University of Leiden Leiden Netherlands University of Muenster Muenster Germany

ISBN: (数字)9783031316715

ISBN: (纸本)9783031316708

Fairness is a crucial concept in the context of artificial intelligence ethics and policy. It is an incremental component in existing ethical principle frameworks, especially for algorithm-enabled decision systems. Yet, translating fairness principles into context specific practices can be undermined by multiple unintended organisational risks. This paper argues that there is a gap between the potential and actual realized value of AI. Therefore, this research attempts to answer how organisations can mitigate AI risks that relate to unfair decision outcomes. We take a holistic view by analyzing the challenges throughout a typical AI product life cycle while focusing on the critical question of how rather broadly defined fairness principles may be translated into day-to-day practical solutions at the organizational level. We report on an exploratory case study of a social impact microfinance organization that is using AI-enabled credit scoring to support the screening process to particularly financially marginalized entrepreneurs. This paper highlights the importance of considering the strategic role of the organisation when developing and evaluating fair algorithm- enabled decision systems. The proposed framework and results of this study can be used to inspire the right questions that suit the context an organisation is situated in when implementing fair AI. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Life cycle

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business User-Oriented Recommender System of Data 17th

Business User-Oriented Recommender System of Data

引用

17th International Conference on Research Challenges in information Sciences, RCIS 2023

作者： Pinon, Sarah NaDI Namur Digital Institute University of Namur Namur Belgium

ISBN: (纸本)9783031330797

Companies nowadays are increasingly dependent on data. In an environment that is more dynamic than ever, they are looking for tools to leverage those data and obtain valuable information in a rapid and flexible way. One way to achieve this is by using Data-Driven Decision Support Systems (Data-Driven DSS). In this project, I focus on one such type of DSS, namely the Self-Service business Intelligence (SSBI) Systems. These systems are designed specifically to avoid the involvement of the IT department when creating business reports by empowering businesspeople in the production of their own reports, thereby reducing the time-to-release of a given report and improving the responsiveness of companies. business decision-makers, when developing their own reports, however face barriers. These challenges are related to the current self-service features that are not sufficiently adapted to their business needs and their lack of technical knowledge. The objective of my project is to build a framework based on Artificial Intelligence (AI) techniques such as Natural Language processing techniques, Semantic and Recommender Systems to solve one of the main challenges faced by businesspeople, namely: the data picking within technical and large current databases. These AI systems offer a number of benefits that are strongly linked to the problems encountered by business users in the data picking process. This paper introduces the three main research questions of my thesis and positions them in the current literature. It then elaborates on the different theoretical, methodological and empirical contributions I plan to advance as part of my project. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Recommender systems

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Influence of Demographic Variables and Usage Behaviour on the Perceived User Experience 1

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18th International Conference on Web information Systems and Technologies, WEBIST 2022

作者： Kollmorgen, Jessica Schrepp, Martin Thomaschewski, Jörg University of Applied Sciences Emden/Leer Emden Germany SAP SE Walldorf Germany

ISBN: (数字)9783031430886

ISBN: (纸本)9783031430879

Users form an overall impression concerning the user experience (UX) based on their perception of special UX qualities. Therefore, measuring users’ perceptions of these particular UX aspects is essential for determining the UX of a product. The measured hedonic qualities, e.g. stimulation or aesthetics, and pragmatic qualities, e.g. efficiency or learnability, form a suitable overall impression of the perceived user experience of the product. In practice, the measurement of such qualities is often carried out with the help of standardized questionnaires such as the SUS, UMUX, or UEQ. However, the same product sometimes shows large differences in the ratings of different users. It is conceivable that other factors, for example, demographics, usage frequency, or experience with a product, can influence UX ratings. In a previous study (Kollmorgen, Schrepp & Thomaschewski, 2022), the four products Netflix, Microsoft PowerPoint, BigBlueButton, and Zoom were examined for differences in the UX ratings according to such factors. In the present paper, the data set was extended by two additional products of different product categories to deepen and broaden the investigation of the influences of external factors on the perceived UX of products, with a specific focus on their impact on pragmatic and hedonic qualities. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Population statistics

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Persuasive Visual Presentation of Prescriptive business Processes 17th

Persuasive Visual Presentation of Prescriptive Business Pro...

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17th International Conference on Research Challenges in information Sciences, RCIS 2023

作者： Leemets, Janna-Liina Kubrak, Kateryna Milani, Fredrik Nolte, Alexander University of Tartu Tartu Estonia Carnegie Mellon University PittsburghPA United States

ISBN: (纸本)9783031330797

Prescriptive process monitoring methods recommend interventions during the execution of a case that, if followed, can improve performance. Research on prescriptive process monitoring so far has focused mainly on improving the underlying algorithms and providing suitable explanations for recommendations. Empirical works indicate, though, that process workers often do not follow recommendations even if they understand them. Drawing inspiration from the field of persuasive technology, we developed and evaluated a visualization that nudges process workers towards accepting a recommendation, following a design science approach. Our evaluation points towards the feasibility of the visualization and provides insights into how users perceive different persuasive elements, thus providing a basis for the design of future systems. © 2023, The Author(s).

关键词： Process monitoring

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Context-Aware Recommender Systems: Aggregation-Based Dimensionality Reduction 17th

Context-Aware Recommender Systems: Aggregation-Based Dimensi...

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17th International Conference on Research Challenges in information Sciences, RCIS 2023

作者： Negre, Elsa Ravat, Franck Teste, Olivier Paris-Dauphine University PSL Research University CNRS UMR 7243 LAMSADE Paris France - Université Toulouse Capitole Toulouse France Université Toulouse 2 Toulouse France

ISBN: (纸本)9783031330797

Context-aware recommender systems (CARS) rest on a multidimensional rating function: Users × Items × Context → Ratings. This multidimensional modelling should improve the quality of the recommendation process, but unfortunately, it is rare or even impossible to have ratings for all possible cases of context. Our objective is therefore twofold: (i) to reduce the dimensionality of the contextual information (in order to reduce the sparsity), which leads to (ii) propose a technique for aggregating the ratings associated with the aggregated dimensions. To do this, we organize, in the CARS utility matrix, the contextual information according to hierarchical dimensions as is done in OLAP (OnLine Analytical processing) and we use a regression-based approach for the rating aggregation according to previously defined hierarchies. Our approach supports multiple dimensions and hierarchical aggregation of ratings. It was validated on two real world datasets. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Coherent scattering

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Interoperability of Open Science Metadata: What About the Reality? 17th

Interoperability of Open Science Metadata: What About the ...

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17th International Conference on Research Challenges in information Sciences, RCIS 2023

作者： Dang, Vincent-Nam Aussenac-Gilles, Nathalie Megdiche, Imen Ravat, Franck Université de Toulouse Toulouse France Université Toulouse 1 Capitole Toulouse France INU Champollion Albi France

ISBN: (纸本)9783031330797

Open Science aims at sharing results and data widely between different research domains. Interoperability is one of the keys to enable the exchange and crossing of data between different research communities. In this paper, we assess the state of the interoperability of Open Science datasets from various communities. The diversity of metadata schemata of these datasets from different sources does not allow for native interoperability, highlighting the need for matching tools. The question is whether current metadata schema matching tools are sufficiently efficient to achieve interoperability between existing datasets. In our study, we first define our vision of interoperability by transversally considering the technical and semantic aspects when dealing with metadata schemata coming from various domains. We then evaluate the interoperability of some datasets from the medical domain and Earth system study domain using acknowledged matching tools. We evaluate the performance of the tools, then we investigate the correlation between various metrics characterizing the schemata and the performance related to their mapping. This paper leads to identify complementary ways to improve dataset interoperability: (1) to adapt mapping algorithms to the issues raised by metadata schema matching;(2) to adapt metadata schemata, for instance by sharing a core vocabulary and/or reusing existing standards;(3) to combine various trends in a more complex interoperability approach that would also make available and operational the (RDA) crosswalks between schemata and that would promote good practices in metadata labeling and documentation. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Data integration

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From Perceived Mobility to the Intention to Use Mobile Payments: The Role of Positive and Negative Determinants 1

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11th International Workshop on Enterprise Applications, Markets and Services in the Finance Industry, FinanceCom 2022

作者： Dzelalija, Petar Ivanisevic Hernaus, Ana Audit Services KPMG Croatia Zagreb10000 Croatia Faculty of Economics and Business University of Zagreb J. F. Kennedy 6 Zagreb10000 Croatia

ISBN: (数字)9783031316715

ISBN: (纸本)9783031316708

Mobile payments have become an important service and tool for managing personal finance in the digital era. However, there is a dearth of research focused on underlying mechanisms and boundary conditions driving a consumer’s decision to use mobile payments for everyday transactions. Therefore, by departing from TAM and TRAM frameworks, we investigated the predictive role of mobile payment antecedents. Both moderating and/or mediating effects were examined through conditional process analyses on the field survey sample of 218 financially educated individuals. We confirmed the mediating role of mobile payment knowledge in the relationship between perceived mobility and intention to use mobile payments, as well as moderating roles of perceived compatibility and perceived risk. Moreover, we were able to validate our comprehensive research model and extend the demographic and regional scope of the related research, going beyond the mainstream findings focused on generation X or Z consumers from emerging and developing markets. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Electronic money

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Towards a Secure and Privacy Compliant Framework for Educational Data Mining 17th

Towards a Secure and Privacy Compliant Framework for Educ...

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17th International Conference on Research Challenges in information Sciences, RCIS 2023

作者： Eleni, Polydorou Privacy Engineering and Social Informatics Laboratory Department of Cultural Technology and Communication University of the Aegean University Hill Mytilene81100 Greece

ISBN: (纸本)9783031330797

Digital education technology has become an essential component of the educational process and has greatly impacted the learning experience in schools and higher education. Especially, in recent years, there has been a surge in the adoption of educational applications and the use of e-learning platforms resulting in a vast amount of educational data being generated. Using Learning Analytics and Educational Data Mining can assist in extracting valuable information from educational data, which can enhance the learning experience for both learners and educators. However, there is a growing need to address privacy concerns and ensure data security, and thus research focus has shifted to the development of privacy frameworks and principles to ensure data privacy and security. This paper highlights the significance of data protection and privacy regulations, such as GDPR, in utilizing data mining methods in educational environments aiming on establishing the foundations for the creation of a privacy-focused framework for data processing within the educational platform. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Data mining

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Privacy Pattern Catalog Approach for GDPR Compliant Appliance: From Legal Requirements to Technology Design 1

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15th PLAIS EuroSymposium on Digital Transformation, PLAIS EuroSymposium 2023

作者： Waidelich, Lukas Schuster, Thomas Pforzheim University Tiefenbronner Str. 65 Pforzheim75175 Germany

ISBN: (数字)9783031435904

ISBN: (纸本)9783031435898

Digital services must adapt to new developments in technology, policy, and compliance regulations. Data protection plays a critical role, making the implementation of privacy-aware services essential. However, small and medium-sized enterprises struggle with meeting data protection requirements. In this paper, we address the challenges posed by the GDPR and compare them with existing solutions. Additionally, we discuss mechanisms to translate legal requirements into technological design. Our approach utilizes patterns as foundational guides to assist in the efficient implementation and application of data protection measures. This article introduces four patterns expanding our collection of data protection patterns. Privacy patterns facilitate compliance with regulations during development and operation. Creating a pattern catalog for data protection is the next logical step. We outline an approach for its development. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Data privacy

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